NRAP
National Risk Assessment Partnership
Rules and Tools Crosswalk: A
Compendium of Computational Tools to
Support Geologic Carbon Storage
Environmentally Protective UIC Class VI
Permitting
31 May 2022
U.S. DEPARTMENT OF
ENERGY
v>EPA
N=
TL
NATIONAL
TECHNOLOGY
LABORATORY
Office of Fossil Energy
and Carbon Management
N RAP-TRS-l-001 -2022
DOE/NETL-2022/3731
EPA-900-B-22-001
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Disclaimer
This project was funded by the United States Department of Energy, National Energy
Technology Laboratory, in part, through a site support contract. Neither the United States
Government nor any agency thereof, nor any of their employees, nor the support
contractor, nor any of their employees, makes any warranty, express or implied, or
assumes any legal liability or responsibility for the accuracy, completeness, or usefulness
of any information, apparatus, product, or process disclosed, or represents that its use
would not infringe privately owned rights. Reference herein to any specific commercial
product, process, or service by trade name, trademark, manufacturer, or otherwise does
not necessarily constitute or imply its endorsement, recommendation, or favoring by the
United States Government or any agency thereof. The views and opinions of authors
expressed herein do not necessarily state or reflect those of the United States Government
or any agency thereof.
Additionally, neither Lawrence Livermore National Security, LLC, the Regents of the
University of California, nor Battelle Memorial Institute, nor any of their employees
makes any warranty, expressed or implied, or assumes any legal liability or responsibility
for the accuracy, completeness, or usefulness of any information, apparatus, product, or
process disclosed, or represents that its use would not infringe privately owned rights.
Reference herein to any specific commercial product, process, or service by trade name,
trademark, manufacturer, or otherwise does not necessarily constitute or imply its
endorsement, recommendation, or favoring by the Lawrence Livermore National
Security, LLC or the Regents of the University of California or Battelle Memorial
Institute. The views and opinions of authors expressed herein do not necessarily state or
reflect those of Lawrence Livermore National Security, LLC, the Regents of the
University of California, or Battelle Memorial Institute and should not be used for
advertising or product endorsement purposes.
Disclaimers for the computational tools contained within this report can be found in their
respective user manuals.
Cover Illustration: Simplified cross section of a geologic carbon storage computational model.
Suggested Citation: Lackey, G.; Strazisar, B. R; Kobelski, B.; McEvoy, M.; Bacon, D. H.;
Cihan, A.; Iyer, J.; Livers-Douglas, A.; Pawar, R; Sminchak, J.; Wernette, B.; Dilmore, R. M.
Rules and Tools Crosswalk: A Compendium of Computational Tools to Support Geologic Carbon
Storage Environmentally Protective UIC Class VIPermitting', NRAP-TRS-I-001-2022;
DOE.NETL-2022.3731; NETL Technical Report Series; U.S. Department of Energy, National
Energy Technology Laboratory: Pittsburgh, PA, 2022;
p 120. DOI: https://doi.org/10i2172/l870412
An electronic version of this report can be found at:
https://netl.doe.gov/enersy-analysis/search
https://edx.netl. doe, gov/nrap
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Rules and Tools Crosswalk: A Compendium of Computational Tools to
Support Geologic Carbon Storage Environmentally Protective UIC Class VI
Permitting
Greg Lackey1'2, Brian R. Strazisar1, Bruce Kobelski3, Molly McEvoy3, Diana H. Bacon4,
Abdullah Cihan5, Jaisree Iyer6, Amanda Livers-Douglas7, RajeshPawar8, Joel Sminchak9,
Benjamin Wernette10, Robert M. Dilmore1
National Energy Technology Laboratory, 626 Cochrans Mill Road, Pittsburgh, PA 15236-0940, USA
2NETL Support Contractor, 626 Cochrans Mill Road, Pittsburgh, PA 15236-0940, USA
3U.S. Environmental Protection Agency, 1200 Pennsylvania Avenue, NW, Washington, DC 20460, USA
4Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA 99352, USA
5Lawrence Berkeley National Laboratory, 1 Cyclotron Road Berkeley, CA 94720, USA
6Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA 94550, USA
7University of North Dakota Energy & Environmental Research Center, 15 North 23rd Street, Stop 9018,
Grand Forks, ND, 58202-9018, USA
8Los Alamos National Laboratory, Earth and Environmental Sciences, Mail Stop T-003, Los Alamos, NM
87545, USA
9Battelle, Columbus, OH 43201, USA
10Southern States Energy Board 6325 Amherst Court Peachtree Corners, GA 30092, USA
NRAP-TRS-I-001-2022
DOE/NETL-2022/3731
Level I Technical Report Series
31 May 2022
NETL Contacts:
Brian R. Strazisar, Principal Investigator and NRAP Technical Portfolio Lead
Kirk Gerdes, Acting Associate Director, Geological & Environmental Systems
Bryan Morreale, Associate Laboratory Director for Research & Innovation, Research & Innovation
Center
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Rules and Tools Crosswalk
Table of Contents
EXECUTIVE SUMMARY 1
1. INTRODUCTION 2
2. CROSSWALK 6
3. FUTURE WORK 15
4. REFERENCES 17
APPENDIX A-l
i
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Rules and Tools Crosswalk
List of Tables
Table 1: Summary of Class VI Rule Requirements 4
Table 2: List of Considered Computational Tools Useful for Class VI Permitting Categorized by
Type 7
Table 3: Crosswalk Between Class VI Permit Elements and Considered Computational Tools. 11
ii
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Rules and Tools Crosswalk
Acronyms and Abbreviations
Term
Description
AIM
Aquifer Injection Modeling
AoR
Areaof review
CMG
Computer Modeling Group
CCS
Carbon Capture and Storage
CO 2
Carbon dioxide
C02BRA
C02 Brine Relative PermeabilityAccessible Database
C02-SCREEN
CO2 Storage prospective Resource Estimation Excel aNalysis
CUSP
Carbon Utilization and Storage Partnershipof the Western United States
CSIL
Cumulative Spatial Impact Layers
DOE
U.S. Departmentof Energy
DREAM
Designs for Risk Evaluation and Management
E4D
4D Geophysical Modelingand Inversion Code
EASiTool
Enhanced Analytical SimulationTool
EDX
Energy Data exchange
EM
Electromagnetic
EMGeo
Electromagnetic-data Geologic Mapper
EPA
U.S. Environmental Protection Agency
ERT
Electrical resistivitytomography
FECM
Fossil Energy and Carbon Management
FEHM
Finite Element Heat& MassTransferCode
FEMA
Federal Emergency Management Agency
HAST
Heatand Salinity Transport
GWB
Geoche mist's Workbench
GCS
Geologic carbon storage
GSDT
Geologic Sequestration DataTool
IMI
Infrastructure Model and Inversion Module
IP
Induced polarization
IP
Interactive Petrophysics
IPCC
Intergovernmental Panelon Climate Change
LANL
Los Alamos National Laboratory
LBNL
Lawrence Berkeley National Laboratory
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Rules and Tools Crosswalk
Acronyms and Abbreviations (cont.)
Term
Description
LLNL
Lawrence Livermore National Laboratory
MATLAB
MATrix LABoratory
MODFLOW
Modular Three-Dimensional Finite-Difference Groundwater Flow Model
MRCI
Midwest Regional Carbon Initiative
MRST
Matrix Laboratory (MATLAB) ReservoirSimulationTool
MVA
Monitoring, Verification, and Accounting
NETL
National Energy Technology Laboratory
NRAP
National Risk Assessment Partnership
NUFT
Nonisothermal, Unsaturated Flow and Transport
Open-IAM
Open-source Integrated Assessment Model
PCOR
Partnership
Plains CO2 Reduction Partnership Initiative to Accelerate Carbon Capture,
Utilization, and Storage Deployment
pGEMINI
parallel Geophysical Electromagnetic Modeling and Inversion of Natural and
Induced sources
PHREEQC
PH Redox Equilibrium (in C language)
PISC
Post-injection site care
PNNL
Pacific Northwest National Laboratory
RCSP
Regional CarbonSequestration Partnerships
SALSA
Semi-Analytical Leakage Solutions for Aquifers
SGeMs
Stanford Geostatistical Modeling Software
SECARB-USA
Southeast Regional Carbon Utilization and Storage Partnership
SIMPA
Spatially Integrated Multivariate Probabilistic Assessment
SOSAT
State of Stress Analysis Tool
STOMP
SubsurfaceTransportOver Multiple Phases
STSF
Short-term Seismic ForecastingTool
TESLA
The EvidenceSupport LogicApplication
TOUGH
TransportOf Unsaturated Groundwaterand Heat
TPFLOW
Two-Phase Flow Model
UIC
Underground injection control
U.S.
United States
USDW
Underground source of drinking water
USGS
United States Geological Survey
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Rules and Tools Crosswalk
Acknowledgments
This work was completed as part of the National Risk Assessment Partnership (NRAP) project.
Support for this project came from the U.S. Department of Energy's (DOE) Office of Fossil
Energy and Carbon Management (FECM). The authors wish to acknowledge the U.S. DOE
FECM for programmatic guidance and support, including Mark Ackiewicz (Director, Office of
Carbon Management Technologies), John Litynski (Director, Division of Carbon Capture and
Storage, DOE Office of Fossil Energy and Carbon Management), Darin Damiani (Carbon
Storage Program Manager, Division of Carbon Storage and Transport), and Sarah Leung
(Carbon Transport and Storage Engineer, Division of Carbon Storage and Transport). The
authors also acknowledge the technical guidance and support of Mark McKoy, Carbon Storage
Technology Manager in the U.S. DOE National Energy Technology Laboratory's (NETL) Office
of Science and Technology Strategic Plans and Programs.
This work was performed partly under the auspices of the U. S. DOE by Lawrence Livermore
National Laboratory under Contract DE-AC52-07NA27344.
The material and suggestions contributed by the Plains CO2 Reduction Partnership Initiative to
Accelerate Carbon Capture, Utilization, and Storage Deployment (PCORPartnership) is based
upon work and lessons learned supported by U.S. DOE's NETL under Award No. DE-
FE0031838 and the North Dakota Industrial Commission (NDIC) under ContractNos. FY20-
XCI-226 and G-050-96. The PCOR Partnership would like to thank Amanda Livers-Douglas,
Tao (Todd) Jiang, Sofiane Djezzar, Steve Emerson, Nessa Mahmood, Neil Dotzenrod, and
Santosh Patil specifically for their contributions.
Southern States Energy Board would like to acknowledge the support of DOE's NETL under
Award No. DE-FE0031830 as well as the Southeast Regional Carbon Utilization and Storage
Acceleration Partnership (SEC ARB-USA) project team. SEC ARB-USA's contribution to this
effort was formulated with the assistance of Sue Hovorka from the University of Texas at
Austin's Bureau of Economic Geology and Anne Oudinot from Advanced Resources
International.
Contributions for providing modeling tool information and draft report comments and edits from
the EPA UIC Program staff in Regions 4, 5, 6, 8, and 9 and the Office of Groundwater and
Drinking Water at EPA Headquarters, Washington, DC.
The authors also wish to acknowledge Delphine Appriou, AnharKarimjee, Jordan Kislear, Kayla
Kroll, George Peridas, Brandon Schwartz, Megan Smith, Jeff Wagoner, and Xianjin Yang.
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Rules and Tools Crosswalk
EXECUTIVE SUMMARY
This report identifies computational tools useful for addressing aspects of the dedicated carbon
storage (Class VI) well permit application under the U. S. Environmental Protection Agency's
(EPA) Underground Injection Control (UIC) Program.
The survey was conducted by researchers of the National Energy Technology Laboratory's
(NETL) Research and Innovation Center in collaboration with representatives of the U. S. EPA,
Lawrence Berkeley National Laboratory (LBNL), LawrenceLivermoreNational Laboratory
(LLNL), Los Alamos National Laboratory (LANL), Pacific Northwest National Laboratory
(PNNL), and the four Regional Initiatives to Accelerate Carbon Capture, Utilization, and
Storage: Carbon Utilization and Storage Partnership of the Western United States (CUSP), Plains
C02 Reduction Partnership Initiative to Accelerate Carbon Capture, Utilization, and Storage
Deployment (PCOR Partnership), Midwest Regional Carbon Initiative (MRCI), and the
Southeast Regional Carbon Utilization and Storage Partnership (SECARB-USA).
Experts from each of these institutions used their knowledge of, and experience with, the UIC
Class VI permit application to identify valuable computational tools. Information was collected
by compiling individual fact sheets for each tool completed by the various contributing
organizations. A total of 59 tools were identified through the elicitation for this report. The fact
sheets for each tool are included in the Appendix. The body of this report provides a brief
summary of UIC Class VI permit application elements and tables that cross-reference the
computational tools with their general application (Table 2) and their relevance to elements of
the Class VI permit application (Table 3). The report concludes by identifying gaps and possible
areas for future investigation.
This report is intended to serve as a reference that can be used by geologic carbon storage
stakeholders to identify computational tools that may be used to develop Class VI permit
applications. The list of computational tools compiled herein is not intended to be exhaustive.
References to any computational tool, service, and/or company are not intended to be
endorsements of those tools, services, and/or companies. Furthermore, failure to reference a
computational tool, service, and/or company is not intended as a repudiation of that
computational tool, service, or company. In addition to this report, information contained herein
will also be made available online through NETL's Energy Data Exchange (EDX) and updated
periodically as new information on relevant computational tools becomes available.
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Rules and Tools Crosswalk
1. INTRODUCTION
Carbon capture and storage (CCS) technology is capable of substantially reducing atmospheric
emissions of carbon dioxide (C02) from power plants and other large point-source emitters
(IPCC, 2005). Deployment of CCS at a scale that will impact global carbon budgets will require
numerous commercial-scale geologic carbon storage (GCS) operations. Some of these operations
are expected to store on the order of one hundred million metric tons of CO2 (National
Academies of Sciences, Engineering, and Medicine, 2021). GCS operations rely on one or more
injection wells to safely deliver large volumes of C02 into deep underground formations (e.g.,
saline aquifers) (IPCC, 2005). Recognizing the unique conditions under which dedicated GCS
wells operate, the U. S. Environmental Protection Agency (EPA) defined a new classification of
injection wells (Class VI) under its Underground Injection Control (UIC) Program for GCS
injection, with Federal Requirements found at 75 FR 77230, December 10,2010, and codified in
the U.S. Code of Federal Regulations (40 § CFR 146.81 etseq.). The Class VI well standard is
intended to facilitate implementation of GCS while protecting underground sources of drinking
water. U.S. EPA regulations define specific requirements for siting, construction, operation,
testing, monitoring, and closure of Class VI wells. A summary of the Federal Class VI Rule
Requirements is shown in Table 1.
The U.S. Department of Energy's (DOE) Office of Fossil Energy and Carbon Management
(FECM) Carbon Storage Program has funded efforts to understand the risks associated with
GCS. The U.S. DOE FECM released a set of Best Management Practices for GCS (NETL,
2017), which shared insights from research and their Regional Carbon Sequestration Partnerships
(RCSP) field laboratory initiative. These documents outline essential activities common to the
success of all GCS projects, including:
• Monitoring, Verification, and Accounting (MVA) for Geologic Storage Projects
• Public Outreach and Education for Geologic Storage Projects
• Site Screening, Site Selection, and Site Characterization for Geologic Storage Projects
• Risk Management and Simulation for Geologic Storage Projects
• Operations for Geologic Storage Projects
• Geologic Formation Storage Classification
GCS projects are inherently complex. Class VI permit applications are multifaceted and require
input from experts with diverse expertise in geology, geochemistry, petroleum engineering, risk
assessment, finance, and law. Several activities in the permitting process require the use of
advanced computational tools to characterize the reservoir, assess risks, and forecast behavior in
the sub surface throughout the injection and post-injection time periods and beyond. Some of the
computational tools available for Class VI permitting are widely used by GCS stakeholders and
experts in other related industries (e.g., oil and gas exploration and production) and are supported
by commercial enterprises. Other tools have been developed by smaller research and
development communities for specific applications and may be less known and used in practice.
Consequently, prospective GCS site operators can choose from a panoply of available
computational tools to engage in the Class VI permitting process.
The purpose of this report is to provide information on available computational tools that may be
applied to various aspects of the Class VI permit application. This effort was led by the National
Energy Technology Laboratory (NETL) in collaboration with: the U.S. EPA; the five U.S. DOE
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Rules and Tools Crosswalk
National Laboratory members of the National Risk Assessment Partnership (NRAP): Lawrence
Berkeley National Laboratory (LBNL), LawrenceLivermore National Laboratory (LLNL), Los
Alamos National Laboratory (LANL), Pacific Northwest National Laboratory (PNNL); and the
four Regional Initiatives to Accelerate Carbon Capture, Utilization, and Storage: Carbon
Utilization and Storage Partnership of the Western United States (CUSP), Plains C02 Reduction
Partnership Initiative to Accelerate Carbon Capture, Utilization, and Storage Deployment (PCOR
Partnership), Midwest Regional Carbon Initiative (MRCI), and the Southeast Regional Carbon
Utilization and Storage Partnership (SECARB-USA). Each participating organization was asked
to provide a list of computational tools they use to address aspects of the Class VI well
permitting process. NETL removed redundancies from the submitted tool lists and asked each
organization to complete a fact sheet for each tool. Each fact sheet was designed to provide
general information for a particular tool and describes how the tool may be used to address
specific requirements for a Class VI well permit. Fifty-nine individual tools are described in this
report. The Appendix contains the completed fact sheets from the contributing organizations.
This compilation of computational tools is intended as an informational resource for practitioners
seeking to understand or develop a Class VI permit application and is not intended to be
exhaustive. Reference to any computational tool should not be seen as an endorsement of that
tool by the coauthors or their organizations. Similarly, a lack of reference to any tool should not
be seen as a repudiation of that tool by the coauthors or their organizations.
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Rules and Tools Crosswalk
Table 1: Summary of Class VI Rule Requirements (modified f rom EPA, 2018)
Class VI Rule Requirement
Reference
Class VI perm it information
40 CFR 146.82
Providetheinformationthatownersoroperatorsmustsubmitto obtaina Class VIpermit.
Site screeningand characterization (minimum criteria for siting) 40 CFR 146.82(a)(2),(3),(5),(6); 146.83(a)(1)
Establish that the proposed Class VI wells will be located in an area with a suitable geologic system, including
an injection zone of sufficient a real extent, thickness, porosity, and permeability to receive the total
anticipated volume of the carbon dioxide stream and confining zone(s)free of transmissive faults or fractures
and of sufficient a real extent and integrity to contain the injected carbon dioxide stream and displaced
formation flu ids and a How injection at proposed maximum pressures and volumes without initiating or
propagating fractures in the confining zone(s).
Area of review (AoR) and corrective action plan
40 CFR 146.82(a)(4),(13); 146.84
Delineate the AoR - the region where injection operations may endangeran underground source of drinking
water (USDW). Computational modeling that is based on available site characterization, monitoring, and
operational data must be used to accountforthe physical and chemical properties of all phases of the injected
carbon dioxide stream. Prepare an AoR and Corrective Action Planfor delineating the AoR, identifying all
artificial penetrations that may require corrective action, performing all necessary corrective action, and
periodically reevaluating theAoRand amendingtheplan if needed.
Financial assurance demonstration (Financial responsibility)
40 CFR 146.82(a)(14); 146.85
Develop cost estimates for— and identify and provide financial assurance instruments sufficient to fund third -
party implementation of—corrective action on improperly abandoned wells in the AoR, injection well plugging,
post-injection site care(PISC) and site closure activities, and emergency andremedial response.
Proposed well construction
40 CFR 146.82(a)(ll)(12); 146.86
Specify the design materials and construction procedures for Class VI wells using materials that are compatible
with the carbon dioxide stream and subsurface geochemistry over the duration of the Class VI project and
sufficient to prevent interformational fluid movement and the en dangerment of USDWs.
Requirements for logging, sampling, and testing priorto
operation
40 CFR 146.82(a)(8); 146.87
Specify activities, includinglogs, surveys, andtests of the injection well and formations, to be performed before
injection of carbon dioxide commence.
Injection well operating
40 CFR 146.88
Specify measuresforClass VI well operation to ensure that the injection of carbon dioxide does not endanger
USDWs, along with limitations on injection pressure and provisions for automatic shut-off devices.
Mechanical integrity
40 CFR 146.89
Specify procedures for continuous monitoring to demonstrate internal mechanical integrity and annual
external mechanical integrity tests.
Testingand monitoring plan
40 CFR 146.82(a)(15); 146.89; 146.90
Prepare a testing and monitoringplan to verify that the geologic sequestration project is operating as
permitted and is not endangering USDWs, to demonstrate the safe operation of the injection well, and to
monitor changes withing the geologic system (e.g., carbon dioxide plume, pressure front, groundwater
quality).
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Table 1 (cont.): Summary of Class VI Rule Requirements (mo dilled f rom EPA, 2018)
Class VI Rule Requirement
Reference
Reporting
40 CFR 146.91
Design a program forthetimely electronic reporting of Class VI well testing, monitoring, and operating results
and meeting requirements for keeping records.
Injection well plugging plan
40 CFR 146.82(a)(16); 146.92(b)
Specify materials and procedures whereby a Class VI injection well will be properly plugged to ensure that the
well does not become a conduitforfluid movement into USDWs following cessation of injection.
Post-injection sitecare (PlSC)and site closure plan
40 CFR 146.82(a)(17)(18); 146.93
Specify activities for testing and monitoring following cessation of injection. The plan must provide for
monitoring the site for 50 years following the cessation of injection, or for an approved alternative timeframe,
or until it can be demonstrated that no additional monitoring is needed to ensure that the project does not
pose an endangermentto USDWs; andfor plugging the injection and monitoring wells and closing the site
following thatdemonstration.
Emergency and remedial response plan
40 CFR 146.82(a)(19); 146.94
Describethe actions to betaken to address events that may cause endangermentto a USDW or other
resource during the construction, operation, and post-injection phases of the project.
Class VI injection depth waiver
40 CFR 146.95
Demonstrate that injection zones andconfining zones above and below the injection zones sufficiently
protective of USDWs to qualify for waiver of the injection zone depth limitation requiring injection zones to be
beneath the lowermost USDW. Such demonstrations will use computational modeling to show that USDWs
above and below the injection zone will not be endangered as a result of fluid movement. This modeling
should be conducted in conjunction with the area of review delineation.
Stimulation program
40 CFR 146.82(a)(9)
Describe the stimulation fluids and procedures to be used and a provide evidence that stimulation will not
interfere with containment (EPA, 2014).
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Rules and Tools Crosswalk
2. CROSSWALK
The 59 computational tools in this report are categorized by their primary type in Table 2. A
detailed fact sheet describing each tool is available in the Appendix. Thirteen distinct tool types
were identified: 1) geochemical modeling, 2) geologic model development, 3) geophysical data
interpretation, 4) geospatial analysis, 5) geostatistical analysis, 6) project planning, 7) release,
transport, and receptor response, 8) reservoir simulation, 9) resource estimation, 10) risk
assessment, 11) seismic and geomechanical risk, 12) well test and log interpretation, and 13)
well and pipeline design. Descriptions of these tool types are included in the Appendix.
Many of the tools have a diverse array of capabilities characteristic of multiple tool types. While
the capabilities of each tool are described in their respective fact sheets, they are categorized only
by their primary application to simplify the presentation of this report. Reservoir simulation tools
were the most frequently referenced tool type, with 16 separate responses provided. Other
common tool types addressed seismic and geomechanical risks (7 responses provided) and
geologic model development (7 responses provided).
Class VI permit applications have twelve elements that include: 1) site characterization, 2) Area
of Review and Corrective Action Plan, 3 ) financial assurance demonstration, 4) well construction
details, 5) Pre-Operational Testing Plan, 6) proposed operating conditions, 7) Testing and
Monitoring Plan, 8) the Injection Well Plugging Plan, 9) Post-Injection Site Care and Site
Closure Plan, 10) Emergency and Remedial Response Plan, 11) Injection Depth Waiver
Application, and 12) Aquifer Exemption Expansion (EPA, 2021). Table 3 provides a crosswalk
between the 59 tools and the elements of the Class VI permit application.
Because owners and operators should also demonstrate that an adequate screening-level analysis
was performed to determine thatthe project site is suitable, site screening was included in Table
3. The Pre-Operational Testing Plan was omitted from Table 3 because it pertains primarily to
data collection and quality control. Both the Injection Depth Waiver Application and Aquifer
Exemption Expansion involve demonstration of USDW non-endangerment and have been
combined in Table 3 for simplicity of presentation.
Site Screening (46 responses provided) and Site Characterization (44 responses provided) were
addressed by the largest number of tools in this report. A large number of tools were also
valuable for developing the Area of Review and Corrective Action Plan (40 responses provided),
Post-Injection Site Care and Site Closure Plan (31 responses provided), Testing and Monitoring
Plan (30 responses provided), Emergency Remedial Response Plan (24 responses provided),
proposed operating conditions (22 responses provided), and Injection Depth Waiver/Aquifer
Exemption (17 responses provided). Fewer tools were applicable to the Injection Well Plugging
Plan (8 responses provided), Well Construction Details (6 responses provided), and Financial
Assurance Demonstration (5 responses provided).
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Rules and Tools Crosswalk
Table 2: List of Considered Computational Tools Usefulfor Class VI Permitting Categorized by Type
Tool Name
Abbreviation
Website/Contact
Geochemical Modeling
Geochemist's Workbench
GWB
httDs://www. ewb.com/index.DhD
PH REdox EQuilibrium (in C language)
PHREEQC
httDs://www.uses.eov/software/Dhreeac-version-3
Geologic Model Development
C02 Brine Relative PermeabilityAccessible Database
C02BRA
httDs://edx.netl.doe.eov/hostine/co2bra/
Decision Space 365
httDs://www.landmark.solutions/ds365
EarthVision
httDs://www.dei.com/earthvision-software-for-3d-modeline-and-visualization/
GeoGraphix
httDs://www.everse.com/home/GVERSEGeoGraDhix20194
Petra
httDs://ihsmar kit.com/Droducts/Detra-eeoloeical-analvsis.html
Petrel
httDs://www.software.slb.com/Droducts/Detrel
Voxler
httDs://www.eoldensoftware.com/Droducts/voxler
Geophysical Data 1 nterpretation
4D Geophysical Modeling and Inversion Code
E4D
h ttDS: //www.d n n 1 .bov/d ro iects/e4d
Electromagenetic-Data Geological Mapper
EMGeo
httDs://iDo.lbl.eov/lbnl2265/
HampsonRussell
httDs://www.eeosoftware.tech/hamDsonrussell
Kingdom
httDs://ihsmar kit.com/Droducts/kinedom-seismic-eeoloeical-interDretation-
software.html
parallel Geophysical Electromagnetic Modelingand
Inversion of Natural and Induced sources
pGEMINI
httDs://enerevenvironment.Dnnl.eov/staff/staff info.asD?staff num=3506)
RokDoc
httDs://www.ikonscience.com/Droducts/rokdoc/
Geospatial Analysis
Cumulative Spatial Impact Layers
CSIL
httDs://edx.netl.doe.eov/dataset/cumulative-SDatial-imDact-lavers
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Rules and Tools Crosswalk
Table 2: List of Considered Computational Tools Usefulfor Class VI Permitting Categorized by Type (cont.)
Tool Name
Abbreviation
Website/Contact
Geostatistical Analysis
Stanford Geostatistical Modeling Software
SGeMs
httD://see ms.sourceforee.net/
Surfer
httDs://www.sold ensoftware.com/Droducts/surfer
Project Planning
Designs for Risk Evaluation and Management
DREAM
httDs://eithub.com/Dnnl/DREAM V2
FE/NETL C02 Saline Storage Cost Model
httDs://www.netl.doe.eov/enerev-analvsis/details?id=2403
SimCCS
httDs://www.carbonsolutionsllc.com/software/simccs/
Release, Transport, and Receptor Response
Modular Three-Dimensional Finite-Difference
Groundwater Flow Model (MODFLOW)with Mass
Transport in 3-Dimensions (MT3DMS) or Reactive
Transportin 3-Dimensions(RT3D)
MODFLOW
httDs://www.uses.eov/mission-areas/wate r-re sources/science/modflow-and-
related-Droerams?at-science center obiects=0#at-science center obiects
Semi-Analytical Leakage Solutions for Aquifers
SALSA
httDs://eesa.lbl.eov/Drofiles/abdullah-cihan/
Tfrack
httDs://eesa.lbl.eov/Drofiles/auanlin-zhou/
Reservoir Simulation
Aquifer Injection ModelingToolbox
AIM Toolbox
httDs://www.Dnnl.eov/Droiects/aim-toolbox
Computer ModelingGroup GEM
CMGGEM
httDs://www.cmel.ca/eem
ECLIPSE
httDs://www.software.slb.com/Droducts/ecliDse#sectionFullWidthTable
Enhanced Analytical SimulationTool
EASiTool
httDs://www.ise.utexas.edu/researcher/sevved hosseini
Finite Element Heat and Mass Transfer Code
FEHM
httDs://eith ub.com/lanl/FEHM
GEOSX
httD://www.eeosx.ore/
Heatand Salinity Transport
HAST
httDs://eesa.lbl.eov/Drofiles/abdullah-cihan/
MATLAB ReservoirSimulationTool
MRST
httDs://www.sintef.no/Droiectweb/mrst/down load/
Nexus
httDs://www.landmark.solutions/Nexus-Reservoir-Simulation
8
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Rules and Tools Crosswalk
Table 2: List of Considered Computational Tools Usefulfor Class VI Permitting Categorized by Type (cont.)
Tool Name
Abbreviation
Website/Contact
Reservoir Simulation (cont.)
Nonisothermal, Unsaturated-Saturated Flow and
Transport
NUFT
httDs://iDo.llnl.eov/technoloeies/software/nuft
PFLOTRAN
httDs://bitbucket.ore/Dflotran/Dflotran/wiki/Home
SubsurfaceTransportOver Multiple Phases-CC>2
ST0MP-C02
httDs://www.Dnnl.eov/eet-stomD
TransportOf Unsaturated Groundwaterand Heat
(TOUGH) 3- EC02N/M or iT0UGH2-EC02N/M
TOUGH3-
EC02N/M or
iTOUGH2-
EC02N/M
httDs://marketDlace.lbl.eov/
Transportof Unsaturated Ground water and Heat-
Fast Lagrangian Analysis of Continua
TOUGH-FLAC
httDs://toueh.lbl.eov/: httD://www.itascace.com/software/FLAC3D
Transportof Unsaturated Ground water and Heat
REACT
TO UGH REACT
httDs://toueh.lbl.eov/software/touehreact/
Two-Phase Flow Model
TPFLOW
httDs://eesa.lbl.eov/Drofiles/abdullah-cihan/
Resource Estimation
C02Storage prospective Resource Estimation Excel
aNalysis
C02-SCREEN
httDs://edx.netl.doe.eov/dataset/co2-screen
Offshore C02SalineStorageCalculator
httDs://edx.netl.doe.eov/dataset/offshore-co2-saline-storaee-calculator
Risk Assessment
Federal Emergency Management Agency (FEMA)
Hazus
FEMA Hazus
httDs://www.fema.eov/flood-maDs/Droducts-tools/hazus
NRAP Open-Source Integrated Assessment Model
NRAPOpen-
1AM
httDs://edx.netl.doe.eov/nraD/nraD-ODen-iam/:
httDs://eitlab.com/NRAP/ODenlAM
Spatially Integrated Multivariate Probabilistic
Assessment
SIMPA
httDs://edx.netl.doe.eov/dataset/simDa-tool
The EvidenceSupport LogicApplication
TESLA
httDs://www.auintessa.ore/software/downloads-and-demos/tesla-2.1.1
9
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Rules and Tools Crosswalk
Table 2: List of Considered Computational Tools Usefulfor Class VI Permitting Categorized by Type (cont.)
Tool Name
Abbreviation
Website/Contact
Seismicand Geomechanical Risk
Athena Data Management System
httDs://www.nanometrics.ca/services/Dassive-seismic-monitorine/athena-data-
manaeement-svstem
FaultSlip Potential
httDs://scits.stanford.edu/software
RiskCat
httDs://eitlab.com/NRAP/RiskCat
RSQsim
httDs://prof iles.ucr.edu/iames.diete rich:
httDs://prof iles.ucr.edu/aDD/home/Drofile/keithrd
Seismogenic Index Model
httDs://eith ub.com/RvanJamesSchultz/Seismoeeniclndex:
httDs://eith ub.com/amienan/rseismTLS
Short-Term Seismic Forecasting Tool
STSF
httDs://edx.netl.doe.eov/nraD/short-term-seismic-forecastine-stsf/
State of Stress Analysis Tool
SOSAT
httDs://eithub.com/Dnnl/SOSAT: httDs://edx.netl.doe.eov/nraD/state-of-stress-
analvsis-tool-sosat/
WellTestand Log Interpretation
IHS WellTest
httDs://ihsmarkit.com/Droducts/welltest-reserve-Dta-software.html
Interactive Petrophysics
IP
httDs://www.lr.ore/en-us/iD-well-analvsis-software/
Neuralog
httDs://www.ne uraloe.com/well-loe-dieitizine-software-neuraloe/
Strater
httDs://www.eoldensoftware.com/Droducts/strater
Techlog
httDs://www.software.slb.com/Droducts/techloe
Well and Pipeline Design
PIPESIM
httDs://www.software.slb.com/Droducts/DiDesim
10
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Rules and Tools Crosswalk
Table 3: Crosswalk Between Class VI Permit Elements and Considered Computational Tools
Tool Name
Geochemical Modeling
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Rules and Tools Crosswalk
Table 3: Crosswalk Between Class VI Permit Elements and Considered Computational Tools (cont.)
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Rules and Tools Crosswalk
Table 3: Crosswalk Between Class VI Permit Elements and Considered Computational Tools (cont.)
Tool Name
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Rules and Tools Crosswalk
Table 3: Crosswalk Between Class VI Permit Elements and Considered Computational Tools (cont.)
Tool Name
Seismic and Geomechanical Risk
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Rules and Tools Crosswalk
3. FUTURE WORK
The information collected in this report is derived from a survey administered to members of the
CCS research and development community knowledgeable in GCS site selection, permitting,
development, operation, and closure. Relatively few tools were identified for some elements of
the Class VI permit application (e.g., well design, well plugging, and well stimulation). Input
from the broader GCS community is needed to compile a more complete list of computational
tools that informs these additional aspects of the Class VI permit application. Furthermore, a
detailed analysis of tools used by applicants for specific Class VI permit application data
(including those required to be submitted to the UIC program through the Geologic
Sequestration Data Tool (GSDT)) may be beneficial. This effort could show how data and
information from analyses conducted in support of each element of the permit can be integrated
to effectively and efficiently communicate information on forecasted GCS site performance, and
related uncertainty. Future work may also consider developing an interactive website on NETL's
EDX platform based on the findings of this report. Periodic updates to such a website with
additional submissions of tool descriptions from the GCS community would provide the most
up-to-date resource for Class VI permit applicants. Disseminating information about available
computational tools and their application to the Class VI permitting process will be critical to the
widespread deployment of GCS in the U.S. and will complement the strategic investments of the
U.S. DOE FECM Carbon Storage Program into research and development for CCS deployment
(NETL, 2017).
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4. REFERENCES
EPA. Class VI Permit Application Outline. U.S. Environmental Protection Agency (EPA), 2021.
https://www.epa.gov/uic/class-vi-permit-application-outline (last accessed April 2022).
EPA. Geologic Sequestration of Carbon Dioxide: Underground Injection Control (UIC) Program
Class VI Primacy Manual for State Directors; U.S. Environmental Protection Agency,
2014.
EPA. Underground Injection Control (UIC) Program Class VI Implementation Manual for UIC
Program Directors; EPA 816-R-18-001; U.S. Environmental Protection Agency (EPA),
2018. https://www.epa.gov/sites/default/files/2018-
01/documents/implementation manual 508 010318.pdf.
Federal Requirements Under the Underground Injection Control (UIC) Program for Carbon
Dioxide Geologic Sequestration (GS) Wells. U.S. Code ofFederal Regulations, 75 FR
77230, December 10, 2010.
IPCC. Carbon Dioxide Capture and Storage, Mertz, B., Davidson, O., de Coninck, H., Loos, M.,
Meyer, L., Eds.; Intergovernmental Panel on Climate Change; Cambrige University
Press: Cambridge, United Kingdom andNew York, NY, 2005.
National Academies of Sciences, Engineering, and Medicine. Accelerating Decarbonization of
the U.S. Energy System. The National AcademiesPress: Washington, DC, 2021.
https://doi.org/10.17226/25932
NETL. Best Practices Manuals for Geologic Carbon Storage. U.S. Department of Energy,
National Energy Technology Laboratory, 2017. http s ://www ,n etl. do e. go v/co al/carb on -
storage/strategic-program-support/best-practices-manuals
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APPENDIX
A.l GEOCHEMICAL MODELING
CO2 injection alters the chemistry of the target formation and may trigger precipitation or
dissolution reactions. Tools in this category are primarily used for aqueous geochemical
modeling, which is necessary to evaluating the impact that C02 may have on a formation.
A.l.l Geochemist's Workbench
Tool Name
Geochemist's Workbench (GWB)
Developer/Owner
AqueousSolutions LLC
Tool Type
Geochemical Modeling
Description
An integrated geochemical modeling package used for balancing chemical reactions,
calculating stability diagrams and the equilibrium states of natural waters, tracing reaction
processes, modeling re active transport, plotting the results of these calculations, and
storingthe related data. GWB can couple chemical reaction with hydrologic transport to
produce simulations known as reactive transport models. GWB can calculate flow fields
dynamically or import flow fie Ids as numeric data or calculated directly from the USGS
hydrologicflowcode MODFLOW.
Tool Licensingand
Access
Licensed as a subscription with 3 versions available: professional ($2,599/year), standard
($l,299/year), and essential ($699/year). An additionalchemistryplugin is available
($2.599/vear). httDs://www. ewb.com/index.DhD
Model Input
Groundwatergeochemical analyses
Model Output
One-dimensional (lD)and two-dimensional (2D) simulations of reactive transport in single
and dual-porosity media, including bioreaction, stable isotopes, and migrating colloids.
Results can be graphed and animated. Calculates Eh-pH and activitydiagrams and creates
a spectrum of specialty plots. Balance reactions, calculate equilibrium constants, and
create geochemical spreadsheets.
Risks Behavior
Considered
Risk of mobilization of metals in groundwater and the impacts to groundwater of CO 2 or
brine leakage
Relevant
Permitting Phase
Characterization, riskassessment, and monitoring
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Testing and Monitoring Plan
How the Tool is
Used
Used to assess risk to ground water or surface water in the event of a release of brine or
C02into a USDW. Would be used in risk assessment and to design the monitoring
program.
Last Updated
Subscription to the GWB provides improvements and new capabilities continuously.
Ongoing
Development
The tool is hiehlvsuDDortedand ud to date. httDs://www.ewb.com/suDDort.DhD
Ease of Use
The GWB is designed for personal computers running Microsoft Windows. It is highly
supported with on line tutorials and community interaction. The re is a graphical user
interface.
Computational
Speed
Computational speeds are not limiting. The model runsin minutes
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Tool Verification
httDs://www.nrc.eov/docs/ML0804/ML080430497.Ddf
Related
References
httDs://www.ewb.com/
httDs://www.ewb.com/documentation.php
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A.1.2 PHREEQC
Tool Name
PHREEQCVersion 3
Developer/Owner
David L. Parkhurst. This software is a product of the U.S. Geological Survey(USGS).
Tool Type
Geochemical Modeling
Description
PHREEQC is a software written in the C++ programming language, which is designed to
perform a wide variety of aqueous geochemical calculations. PHREEQC has capabilities for
batch reactions, which include aqueous, mineral, and gas phase, and one-dimensional
(ID) transport calculations. The solubility of gases in gas mixtures at (very) high pressures
and temperatures can be calculated with the Peng-Robinson equation of state (Peng and
Robinson, 1976).
Tool Licensingand
Access
Users donotneeda license or permission from USGSto use this software.
httDs://www.uses.eov/software/Dhreeqc-version-3
Model Input
Formation water chemistry
Formation mineralogical composition
Gas phase (CC>2atformation temperatureand pressure)
Model Output
Change in pH over simulation period
Mineral dissolution/precipitation dueto CO2 reactivity
Change in aqueous and mineralogicalcompositions
Risks Behavior
Considered
Model potential dissolution/reprecipitation of mineralsin the confining layers to evaluate
the geochemical behaviorand compatibilityof the injectedCC>2Stream with the rocks and
fluids in the confiningzones
Relevant
Permitting Phase
Site characterization/evaluation
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Testing and Monitoring Plan
How the Tool is
Used
A vertically oriented ID transport simulation model is created using a stack of mu Itiple
cells; typically each cell is 1 meter in thickness. The confining intervals are exposed to CO 2
at the top and bottom boundaries of the injection zone, and CO 2 is allowed to enter the
PHREEQC confining zone model by diffusion and/or advection/dispersion processes. For
cap rocks at the top ofthe C02storage reservoir, the simulation considers molecular
diffusion in a single aqueous phase as the dominant mass transport process. No advection
is assumed in the modeled system (no netflowof formation water/brine). Forconfining
rocks at the bottomofthe C02Storage reservoir, the simulation considers an advection-
dispersion transport mechanism in an aqueous phase as the dominant mass transport
process (dissolved CO2 through the water-saturated pore space). Results are calculated at
the center of each cell starting from the confining layer-C02 exposure boundary. The
simulations are based on mass balance laws that include all the species present in the
specific CO 2 storage site sand their cor responding equilibrium constants. Each cell is
defined by the specificmineralogicalcompositionof the confining rocks obtainedfrom
the X-ray diffraction (XRD) analysis of core samples.
Last Updated
August2021
Ongoing
Development
Ongoing minor development (for instance: existing database/basic functions
development)
Active usercommunity
Ease of Use
PHREEQC has a graphical user interface that is easy to follow.
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Computational
Speed
Fast computational speed (not more than a couple of minutes)
Tool Verification
Tool verified by multiple authors and published research articles (see below).
Related
References
Gaus, 1.; Azaroual, M.; Czernichowski-Lauriol, 1. Reactive transport modelling of the impact
of CO2 injection on the clayey cap rock atSleipner(North Sea). Chemical Geology
2005,217,319-337.
Hemme,C.; Van Berk, W. Change in cap rockporosity triggered by pressureand
temperature dependent CO2-water-rockinteractions in CO2 storage systems.
Petroleum 2017,3,96-108.
Parkhurst, D. L.; Appelo, C. A.J. Description of input for PHREEQC version 3 - a computer
program for speciation, batch-reaction, one-dimensional transport, and inverse
geochemicalcalculations; U.S. Geological Survey: Denver, CO, 2013.
Peng, D. Y.; Robinson, D. B. A new two-constant equation of state. Industrial &
Engineering Chemistry Fundamentals 1976,15,59-64.
Talman,S.; Perkins, E.; Wigston, A.; Ryan,D.; Bachu,S. 2013, Geochemicaleffects of
storing CO 2 in the Basal Aquifer that underlies the Prairie Region in Canada.
Energy Procedia 2013,37,5570-5579.
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A.2 GEOLOGIC MODEL DEVELOPMENT
Geologic modeling is a necessary aspect of the Class VI well permitting process that requires
diverse input from multiple data sources. Tools in this category synthesize a diverse array of
information for the building and visualization of three-dimensional (3D) geologic models.
A.2.1 CO2BRA
Tool Name
CO2 Brine Relative PermeabilityAccessible (CO2BRA) Database
Developer/Owner
NETL Research and Innovation Center
Tool Type
Geologic Model Development
Description
Relative permeability data is poorly described in the literature yet is critical to describe
multiphase subsurface transport. This database provides core and experimental details of
unsteady relative permeability measurements of super-critical CO 2 and brine through rock
coresfrom a wide variety of depositional environments.
Tool Licensingand
Access
Open datasets are available on: httDs://edx.netl.doe.eov/hostine/co2bra/
Model Input
Depositional environment and/or reservoir properties (porosity, permeability, etc.) of
desired properties
Model Output
Relative permeability curves for model incorporation
Risks Behavior
Considered
Multiphase transport
Relevant
Permitting Phase
Site characterization and screening
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan, Testing and
Monitoring Plan, Post-lnjectionSite Care and Site Closure Plan
How the Tool is
Used
Identify most relevant core data to apply to site, download. and utilize relative permeability
curves in reservoir models
Last Updated
Summer 2021
Ongoing
Development
Ongoing additions of new core flow data as available
Ease of Use
Data isdownloadable in spreadsheetoraccessiblerightfromaweb browser
Tool Verification
Documentation on website describes processing methods
Related
References
Moore, J.; Crandall, D.; Holcomb, P. Relative Permeabilityin Reactive Carbonate Rock.
International Society of Porous Media (InterPore) 13th Annual Meeting, May 31-
June 4.
Moore, J.; Crandall, D.; Holcomb, P.; Workman,S. Unsteady-stateC02-Brine relative
permeability measurements of reactive cores. 2020 Fall American Geophysical
Union Meeting,San Francisco, CA, Dec 7-11,2020.
Moore, J.; Holcomb, P.; Crandall, D.; King, S.; Choi, J.-H.; Brown, S.; Workman, S. Rapid
determination of relative permeability curves for brine and supercritical CO2
systems using CT and unsteady state flow methods. Advances in Water Resources
2021.
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A.2.2 Decision Space 365
Tool Name
Decision Space 365
Developer/Owner
Halliburton/Landmark Graphics Corporation
Tool Type
Geologic Model Development
Description
The tool has functionality for data loading, seismicand well based interpretation,
kinematic modeling, petrophysics, seismic processing, and static/geologic modeling
Tool Licensingand
Access
Commercial licensine: httDs://www.landmark.solutions/ds365
Model Input
Geologic datatypes, notlimited to butincludingseismic, well log and interpretation,
contour and structure information, and conceptual model inputs
Model Output
Afaciesand petrophysical geologic model exported as inputto flow model
Risks Behavior
Considered
Geologic lithotypesand reservoir heterogeneity
Relevant
Permitting Phase
Site characterization, site screening
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan, Well
Construction Details
How the Tool is
Used
Screening of site and reservoir characterization by multi-disciplinary team with Realtime
interpretation updatesacrossteam
Last Updated
September2021
Ongoing
Development
Yes
Ease of Use
Integrated userenvironmentwith client/server configurations. Includesvisual workflow
assistantand training.
Computational
Speed
The performance scales to the workload based on size of problem. The software is
designed to handle both small and large problems.
Tool Verification
Industry certified subsurface tool used to measure and record reservoir capacities
Related
References
www.landmark-solutions.com
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A.2.3 EarthVision
Tool Name
EarthVision
Developer/Owner
Dynamic Graphics Inc.
Tool Type
Geologic Model Development
Description
EarthVision is a software for 3D model building, analysis, and visualization, with precise
3D models that can be quicklycreated and updated. Accurate mapsand cross-sections,
reservoir characterization, and volumetricanalysisare made easy. Earth Vision's advanced
3D/4D Viewer enables model examination and interrogation in the context of datasets
from throughout the asset development team, which serves to improve and simplify
quality control, well planning,and communication to management, investors, partners,
and other team members.
Tool Licensingand
Access
Commercial: Contact: httDs://www.dei.com/contact-dvnamic-eraDhics-inc/
Model Input
ASCII data, LAS files, shapefiles. The input is 3D geological information aboutthe number
of layers, their thickness, location of faults, wells, and other information required to
create a model of the subsurface.
Model Output
ASCII data, shapefiles, DGI for matted files. The output is the 3D model itself. The software
allows creation of cross-sections, 2D maps, contours, and calculation of volumes, etc.
Risks Behavior
Considered
Not applicable
Relevant
Permitting Phase
High-level regional models, site screening, site characterization, injection, post-injection,
etc.
Class VI Permit
Element
Addressed
Site Screening, Site Characterization
How the Tool is
Used
The tool is used to create a geological model for the site of interest
Last Updated
EarthVision 12
Ongoing
Development
Yes
Ease of Use
The tool comes with a graphical user interface. Training courses are offered.
Tool Verification
Unable to locate
Related
References
Wagone r, J. 3D Geologic Modeling of the Southern San Joaquin Basin for the Westcarb
Kimberlina Demonstration Project-A Status Report; 2009. doi:10.2172/948987.
Several other references included at httDs://www.dei.com/earthvision-software-for-3d-
modeline-and-visualization/ underthe articles and papers section.
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Rules and Tools Crosswalk
A.2.4 GeoGraphix
Tool Name
GeoGraphix
Developer/Owner
Gverse
Tool Type
Geologic Model Development
Description
GeoGraphixis a completegeoscience platform offeringleading-edge mapping, geological,
geophysical, and petrophysical interpretation, structural modeling, well and field
planning, and state-of-the-art 3D visualization.
Tool Licensingand
Access
Commercial license: httDs://www.everse.com/home/GVERSEGeoGraDhix20194
Model Input
Well logs, seismic, core tests, LAS files, SEGY, SHP files, base maps, we II data
Model Output
Maps, cross sections
Risks Behavior
Considered
Leakage, storage resource, faults, fractures, boundaries
Relevant
Permitting Phase
Site Screening, Site Characterization
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Re vie wand Corrective Action Plan, Financial
Assurance Demonstration, Well Construction Details, Testing and Monitoring Plan,
Injection Well Plugging Plan, Post-Injection Site Care and Site Closure Plan
Last Updated
2019
Ongoing
Development
Commercial, regularupdates
Related
References
httDs://www.eve rse.com/eeoeraDhix
httDs://www.Imkr.com/eeoeraDhix/GVERSE-GeoGraDhix-Brochure.Ddf
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A.2.5 Petra
Tool Name
Petra IHS
Developer/Owner
IHS (Information Handling Services) Markit
Tool Type
Geologic Model Development
Description
Petra is a cost-effective software solution for managing, manipulating, and visualizing
integrated geological, geophysical, and engineering data
Tool Licensingand
Access
Petra Licensine(®ihs.com
PETRAQuoteReauest^ihs.com
Model Input
Depth registered raster images and LAS (Log ASCII Standard) files - digital log curve data
Model Output
Maps of geologic structures within a consistent stratigrap hie framework to increase
knowledge of depositionalenvironments
Risks Behavior
Considered
No risks or behaviors
Relevant
Permitting Phase
Site screening, Site characterization
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Re vie wand Corrective Action Plan, Testing
and Monitoring Plan
How the Tool is
Used
Petra's direct connection to IHS enables the user to download multiple information (3
million U.S. wells, providing current, historical and production data). Mapping (display
contour grids; create customizable maps to assist in reservoir analysis and well location)
and Cross Section (display digital/raster log curves, pick formation tops across a basin or
play; display fault gaps, cored and completed zones; interpolate the value of well logs
between wells) Modules model and analyze the areas of interest.
Last Updated
2020
Ongoing
Development
httDs://ihsmarkit.com/Droducts/Detra-eeoloeical-analvsis.html
CustomerCare (fflihsmarkit.com
Ease of Use
Microsoft Windows Vista/Windows 7 64-bit dual monitor System,
no need for computer programmingskillsto use the tool
Computational
Speed
Computational speeds are not limiting in any way
Related
References
httDs://DetraftD.ihsenerev.com/Petraman.Ddf
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Rules and Tools Crosswalk
A.2.6 Petrel
Tool Name
Petrel
Developer/Owner
Schlumberger
Tool Type
Reservoir Simulation
Description
Petrel is a software platform that allows users to integrate geologic data from many
disciplines to study and characterize reservoirs. Seismic data, geophysical well log data, and
geostatistics can be used to perform well correlation, build detailed reservoir models,
estimate petrophysical properties, calculate volumes, and visualize results.
Tool Licensingand
Access
Commercial proprietary software. On-premise and cloud solutionsavailable. Licensing
options purchasedviacommunication with Schlumberger.
httDs://www.software.slb.com/Droducts/petrel
Model Input
Geophysical we II log data, core data, geologic formation tops, and wellhead data
Model Output
3D reservoir mode Is, including geometric and petrophysical property distributions, 3D
surfaces/maps, well correlations, and seismic interpretations
Risks Behavior
Considered
Parameter uncertainty/sensitivity analysis, geologic uncertainty, and volumetric estimations
Relevant
Permitting Phase
Site screening, site characterization, and application preparation
Class VI Permit
Element
Addressed
Area of Review and Corrective Action Plan, Testing and Monitoring Plan, Post-Injection Site
Care and Site Closure Plan
How the Tool is
Used
Petrel can be used to evaluate and interpret many types of geologic information. It can be
used to estimate geologic properties with nearby legacy data for site screening, creating a
model for feasibilitystudiesand creating a detailed model with site-specific data for
reporting/permit application activities.
Last Updated
August 6,2021 (latest major re lease)
Ongoing
Development
Schlumberger develops, supports, and maintains the software. It is a standard tool in the oil
and gas industry.
Ease of Use
The tool has an interactive graphical user interface. No programming skills are required, but
VBA (Visual Basic for Applications) or SQL (Structured Query Language) experience can be
utilized in Petrelworkflows. Fundamental geologic knowledge is recommended beforeuse.
Geostatistics and/or data analysis experience is a plus.
Computational
Speed
3D modeling can generate loads of varying sizes on computational resources. Generating
models with large cell counts and uncertainty workflows could potentially lead to long
computational times. Basic tasks (loading we II logs, viewing we II logs, generating 3D
surfaces, and geometric properties) are generally not computationally intensive, but a
workstation with adedicatedgraphics processing unit (GPU) is recommended.
Tool Verification
The tool has been used forseveral years throughoutthe oil and gas industry.
Related
References
httDs://www.software.slb.com/Droducts/petrel
httDs://www.software.slb.com/Droducts/Droduct-librarv-
v2?Droduct=Petrel&tab=Case%20Studies
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A.2.7 Voxler
Tool Name
Voxler
Developer/Owner
Golden Software
Tool Type
Geologic Model Development
Description
3D visualization softwarewith utility for subsurface geologicand geophysical data
visualization and interpolation, and functionality to facilitate communication of data and
interpretation to stakeholders
Tool Licensingand
Access
Commercial license: httDs://www.eoldensoftware.com/Droducts/voxler
Model Input
GIS data, map surfaces, geotechnical data
Model Output
3D maps
Risks Behavior
Considered
Leakage, storage resource, faults, fractures, boundaries
Relevant
Permitting Phase
Site screening, site characterization
Class VI Permit
Element
Addressed
Site Screening, Site Characterization Plan, Area of Review and Corrective Action Plan
Last Updated
Version 4.6.913.
Ongoing
Development
Commercial, regularupdates
Related
References
httDs://www.eoldensoftware.com/Droducts/voxler
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A.3 GEOPHYSICAL DATA INTERPRETATION
Geophysical analyses are essential for subsurface characterization and monitoring at GCS sites.
Tools in this category are primarily used to interpret geophysical information (e.g., well logs,
seismic data).
A.3.1 E4D
Tool Name
4D Geophysical Modelingand Inversion Code (E4D)
Developer/Owner
Pacific Northwest National Laboratory (PNNL), Developers: TimothyJohnson, Piyoosh
Jaysaval, Judy Robinson
Tool Type
Geophysical Data Interpretation
Description
Three-dimensional (3D) forwardand inverse modeling of static and time-lapseelectrical
resistivity tomography (ERT), induced polarization (IP), and travel-time tomography for
seismic and ground penetrating radar.
Tool Licensingand
Access
Available for download at httDs://eithub.com/Dnnl/E4D.ThecoDvrieht agreement is
contained within thesourcecode.
An Infrastructure Model and Inversion (IMI) Module is available formodeling of metallic
infrastructure within the geoelectrical run modes. Licenses are available by contacting the
PNNL Commercialization Manager.
Model Input
Geophysical datasets and a priori site information to be used as constraints.
Model Output
3D or four-dimensional (4D) distributions of conductivity and/or velocity.
Relevant
Permitting Phase
Site characterization, injection, and post-injection
Class VI Permit
Element
Addressed
Site Characterization, Testing and Monitoring Plan
How the Tool is
Used
This tool is used to interpret geophysical data to identify any local or regional faulting,
faults, or fractures that could serve as flu id migration pathways, confirming lateral extent
of the reservoir and upper and lowerconfining zones and generating products (depth
horizons and inversion volumes) for use in geologic mode Is to simulate the CO 2 plume to
help establish the area of review.Thetool can also be used to interpret time-lapse
electrical resistivity data to image the CO 2 plume as part of the monitoring program.
Last Updated
Last updated: September2021
Ongoing
Development
E4D is updated with additionalcapabilitiesin response to sponsor needs.
Ease of Use
There is a learning curve to use E4D, mostly due to the flexibility built into the inputs that
allow for its usage in a wide variety of environments. Users should have a general
knowledge of the geophysical applications forwhich E4D is being used.
Computational
Speed
E4D was designed to work in distributed-memory, high-performance computing systems.
It is also highly parallelized. E4Dcan accommodate geophysical surveys with thousands of
measurements and model domains with millions of parameters.
Tool Verification
E4D is NQA-1 qualified from ASME.
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Website: httDs://www.Dnnl.eov/Droiects/e4d
An online usereuide is available at: httDs://e4d-usereuide.Dnnl.eov/index.html
Publications:
Johnson, T. C.; Versteeg, R.J.; Ward, A.; Day-Lewis, F. D.; Revil, A. Improved
Related
hydrogeophysical characterization and monitoringthrough parallel modeling and
References
inversion of time-domain resistivity and induced-polarization data. Geophysics
2010, 75.
Johnson, T. E4D: A distributed memory parallel electrical geophysical modeling and
inversion code User Guide - Version 1.0.; Pacific Northwest National Laboratory,
Richland, WA, 2014
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A.3.2 Electromagnetic-data Geological Mapper (EMGeo)
Tool Name
EMGeo Electromagnetic-data Geological Mapper
Developer/Owner
Lawrence Berkeley National Laboratory (LBNL), Developers: Gregory A. Newman, Michael
Commer
Tool Type
Geophysical Data Interpretation
Description
Forward and inverse modelingof frequency-domain electromagnetic (EM) data.
Supported data types are controlled-source EM, magnetotelluric, and electrical resistivity
tomography (ERT).
Tool Licensingand
Access
Licensed through Technology Transfer of LBNL. It can be purchased by contacting LBNL
TechnoloevTransfer. httDs://iDo.lbl.eov/lbnl2265/
Model Input
Model of electrical resistivity/conductivity of the subsurface
Model Output
The model produces EM data simulations based on the three-dimensional (3D)
resistivity/conductivity distribution.
Risks Behavior
Considered
It can simulate resistivity/conductivity anomalies dueto leakage
Relevant
Permitting Phase
It can be used during all phases of a Class VI permit (e.g., for pre-injection and post-
injection characterization)
Class VI Permit
Element
Addressed
Testingand Monitoring Plan
How the Tool is
Used
The tool can be used within an imaging procedureembedded into a Class VI permitting
workflow. Imaging provides spatial maps of injected fluid flow.
Last Updated
Lastupdated: September 2021.
Ongoing
Development
The tool is still under development. Some companies who have licensed are the current
user community. Support is available.
Ease of Use
There exists a graphical user interface for model viewingand manipulation. Users do not
need computer programming skills to use the tool.General knowledge of geophysical EM
modeling and inversion is helpful.
Computational
Speed
The tool is designed for computational efficiency be cause it is highly parallel. Simulation
times depend on model size, butthey can be scaled if computing resources are available.
Tool Verification
The tool has been verified. Comparative model studies and calibration data inversions are
in journal publications by Commer and Newman.
Related
References
Website: httDs://i do.lbl.eov/lbnl22 65/
Manual available through licensing or request
Publications:
Commer, M.; Newman G. A. New advances in three-dimensional controlled-source
electromagnetic inversion. Geophysical Journal International 2008,172,513-
535.
Commer, M.; Newman G. A. Three-dimensional controlled-source electromagneticand
magnetotelluric joint inversion. Geophysical Journal International 2009,178,
1305-1316.
Commer, M.; Newman G. A.; CarazzoneJ. J.; DickensT. A.; Green K. E.; Wahrmund L. A.;
Willen, D. E.; Shiu J. Massively-parallel electrical-conductivity imaging of
hydrocarbons usingthe Blue Gene/Lsupercomputer. IBM Journal of Research
and Development 2008,52-1/2,93-103.
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A.3.3 HampsonRussell
Tool Name
HampsonRussell
Developer/Owner
Topic us and Vela (previously CGG)
Tool Type
Geophysical Data Interpretation
Description
The software is a suite of reservoir characterization tools that integrates well logs, seismic
data, and geophysical processes foradvanced geophysical interpretation and analysis with
applicability for field developmentand maximizing recovery in mature reservoirs.
Tool Licensingand
Access
The tool is licensed through Flexlm tools on a license server.
httDs://www.eeosoftware.te ch/hamDsonrussell
Model Input
Seismic data (stacked or gather), well logs, and velocities
Model Output
The software generates conditioned seismic data that include attribute volumes,
crossplotting, and interpretation functions for locating AVO (amplitude variation with
offset) anomalies.
Relevant
Permitting Phase
Site characterization, injection, and post-injection
Class VI Permit
Element
Addressed
Site Characterization, Area of Review and Corrective Action Plan
How the Tool is
Used
This tool is used to interpret seismic data to identify any local or regional faulting, faults,
or fracturesthat could serve as fluid migration pathways, confirming lateral extent of the
reservoir and upper and lower confining zones and generating products (depth horizons
and inversion volumes) for use in geologic models to simulate the CO2 plume to help
establish the area of review. The tool can also be used to condition and interpret time-
lapse seismic data to image the CO 2 plume as part of the monitoring program.
Last Updated
June 2021, Version 11.0
Ongoing
Development
The software is still under developmentand offers support.
Ease of Use
The application has a graphical interface. Computer programming is not necessary to use
the application. Advanced understanding of seismicdata is required.
Computational
Speed
The speed varies depending on the size of the project and whether the data are
networked or on a local drive.
Tool Verification
Verification can be found at httDs://www.cee.com/eeosoftware/hamDsonrussell
Related
References
httDs://www.cee.com/eeosoftware/hamDson russell
httDs://www.cee.com/sites/default/files/2020-12/HamDsonRussell%200verview.Ddf
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A.3.4 Kingdom
Tool Name
Kingdom
Developer/Owner
IHS Markit
Tool Type
Geophysical Data Interpretation
Description
Kingdom integrates geoscience, geophysics, and engineering subsurface data into a single
software solution.
Tool Licensingand
Access
Licensed through a proprietary IHS license manager on a license server.
httDs://ihsmarkit.com/Droducts/kinedom-seismic-eeoloeical-interDretation-software.html
Model Input
Seismic data, well data, and well log data
Model Output
A better understandingof the subsurface, with advanced interpretation and visualization
of seismic data
Relevant
Permitting Phase
Site characterization, injection, and post injection
Class VI Permit
Element
Addressed
Site Characterization, Area of Review and Corrective Action Plan
How the Tool is
Used
This tool is used to interpret seismic data to Identify any local or regional faulting, faults,
or fracturesthat could serve as fluid migration pathways, confirming lateral extent of the
reservoir and upper and lower confining zones and generating products (depth horizons)
for use in geologic models to simulate the CO 2 plume to help establish the area of review.
The tool can also be used to interpret time-lapse seismic data to image the C02plumeas
part of the monitoring program.
Last Updated
July2021,Version 2021
Ongoing
Development
The application is still underdevelopment with support. There is an active user
community.
Ease of Use
The application has a graphical interface, and the userdoesnotneed programing skills.
The user will need advanced knowledge of subsurfacegeoscience data.
Computational
Speed
The speed varies depending on the size of the project and whether the data are
networked or on a local drive.
Tool Verification
Verification can be found at: httDs://ihsmarkit.com/Droducts/kinedom-seismic-eeoloeical-
interDretation-software.html
Related
References
httDs://ihsmarkit.com/Droducts/kinedom-seismic-eeoloeical-interDretation-software.html
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A.3.5 pGEMENI
Tool Name
pGEMINI: parallel Geophysical Electromagnetic Modeling and Inversion of Natural and
Induced sources
Developer/Owner
Piyoosh Jaysaval (PNNL)
Tool Type
Geophysical Data Interpretation
Description
Three-dimensional (3D) forward modeling and inversion of frequency-domain
electromagnetic (EM) data.The forward modeling is based on unstructured-meshfinite
element method and the inversion employs a Gauss-Newton optimization method.
Supported data types are active-source EM (e.g., controlled-source EM, airborne EM,
borehole EM) and natural source EM (e.g., magnetotelluric)data.
Tool Licensingand
Access
The code is accessible by request through the developer: Piyoosh Jaysaval
httDs://enerevenvironment.Dnnl.eov/staff/staff info.asD?staff num=3506
Model Input
Forward Modeling: 3D electrical conductivity model of the subsurface
Inversion: Recorded EM data
Model Output
Forward Modeling:Simulated EM data
Inversion: Inverted 3D electrical conductivity model of the subsurface
Risks Behavior
Considered
Monitoring migration of C02or brine through changes in the electricalconductivity.
Relevant
Permitting Phase
All phases of a Class VI permit: pre-and post-injection characterization and monitoring
Class VI Permit
Element
Addressed
Site Characterization, Testing and Monitoring Plan, and Post Injection Site Care and Site
Closure
How the Tool is
Used
pGEMINI can be used to image subsurfaceconductivityfor site characterization or
changes in conductivity for monitoring C02 migration (Site Care).
Last Updated
March 2022
Ongoing
Development
Yes. pGEMINI is a recently developed code, and new capabilities are being added.
Ease of Use
The tool does not have a graphical user interface but can be executed by providing in put
files created using a simple text editor. Computer programming skills are not required, but
an understanding of geophysics, geology, and geophysical EM methods is needed for
better applications.
Computational
Speed
pGEMINI is massively parallelized to reduce computational wall-clock times for large-scale
EM modeling and inversion problems.
Tool Verification
Numerical results are benchmarked against various published results and some of the
benchmarking results are presented in Jaysaval etal. (2022).
Related
References
Jaysaval, P.; Johnson,T.C. pGEMINI: Parallel Geophysical Electromagnetic Modelingand
Inversion for Natural and Induced sources-3-D Forward modeling for active
source. ComputationalGeosciences under review 2022.
Jaysaval, P.; Knox, H.; Chojnicki, K.; Schwering, P.; Winn, C.; Hardwick,C.; Norbeck,J.; Hinz,
N.; Matson, G.; Ayling, B.; Mlwasky, E.; Faulds, J. Feasibility Study of
Magnetotelluricand Controlled-source Electromagnetic Methods for Geothermal
Exploration atSteptoe Valley, NV. Poster presented at the Geothermal Rising
Conference, 2021. https://doi.org/10.5281/zenodo.6326589
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Jaysaval, P.; Robinson, J. L.; Johnson, T.C. Stratigraphic identification with airborne EM
methods at the Hanford Site, Washington. Journal of Applied Geophysics 2021,
192.104398. httDs://doi.ore/10.1016/i.iaDDeeo.2021.104398
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A.3.6 RokDoc
Tool Name
RokDoc
Developer/Owner
Ikon Science
Tool Type
Geophysical Data Interpretation
Description
Geomechanical solutions for accelerating and improvingsubsurface predictions
Tool Licensingand
Access
The tool is licensed through Flexlm tools on a license server.
httDs://www.ikonscience.com/Droducts/rokdoc/
Model Input
Seismic data and well logdata
Model Output
Solutions include rockphysics, reservoircharacterization, pressure prediction, and real-
time drillingmonitoring
Relevant
Permitting Phase
Site characterization, injection, and post injection
Class VI Permit
Element
Addressed
Site Characterization, Testing and Monitoring Plan
How the Tool is
Used
This tool is used to perform flu id substitution modeling to determine the viability of using
time-lapse seismic to monitor the CO 2 plume as part of the monitoring plan. This tool can
also be used for reservoircharacterization and interpretation of time-lapse seismicdata.
Last Updated
June 2021, Version 6.6.3
Ongoing
Development
The application is still underdevelopment with support. There is an active user
community.
Ease of Use
The application hasagraphical interface,and the userdoesnotneed programingskills.
The user will need advanced knowledge of subsurfacegeoscience data.
Computational
Speed
The speed varies depending on the size of the project and whether the data are
networked or on a local drive.
Tool Verification
Verification can be found at https://www.ikonscience.com/Droducts/rokdoc/
Related
References
httDs://www.ikonscience.com/Droducts/rokdoc/
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A.4 GEOSPATIAL ANALYSIS
Mapping the surface footprint of a GCS site is a core requirement of the Class VI permitting
process. Tools in this category are primarily used for mapping and analyzing spatial
relationships.
A.4.1 Cumulative Spatial Impact Layers (CSIL)
Tool Name
Cumulative Spatial Impact Layers™ (CSIL)
Developer/Owner
National Energy Technology Laboratory; Developers: Lucy Romeo, PatrickWingo
Tool Type
Geospatial Analysis
Description
Cumulative Spatial Impact Layers™ (CSIL) is aGIS-based tool that sums spatio-temporal
datasets based on spatial over lap and numeric attributes. Developed as a desktop and
online tool, CSIL applies multiple additive frameworks allowing users to analyze rasterand
vector datasets by calculating data, record, or attribute density. Providing an efficient and
robust method for summarizing disparate, multi-format, multi-source geospatial data,
CSIL addresses the needfor a new integration approach and resultinggeospatial product.
The built-in flexibility of the CSIL tool allows users to answer a range of spatially driven
questions. Use cases include addressing regulatory decision-making needs, risk analysis,
economic modeling, and resource management.
Tool Licensingand
Access
CSIL iscurrentlytrademarked by NETL. It can be freely down loaded from the Energy Date
exchange (EDX) website.
Desktop tool citation:
Romeo, L.; Wingo, P.; Nelson, J.; Bauer, J.; Rose, K. Cumulative Spatial Impact Layers™, Jan
24.2019. httDs://edx.netl.doe.eov/dataset/cumulative-SDatial-imDact-lavers.
DOI: 10.18141/1491843
Model Input
The parameter information provided below is based on the current desktop version.
Ultimately, the user needs only spatial data to complete a CSIL run. Ideally, they will
understand of what the data represents, metadata, and a clear objective in running the
CSIL tool.
• Type of CSIL Analysis-There are three options the usercan select:
1) "Create a Spatial-based CSIL (summarize data presence)" - quantifies the number
of in put spatial datasets that overlap within each grid cell over a spatial extent.
Each dataset is represented in each cell by a 1 if present, or 0 if absent
2) "Create a Spatial-based CSIL (summarize data record density)" - counts the total
number of records per each in put spatial dataset that overlap within each grid
cell over a spatial extent
3) "Create an Attribute-based CSIL (summarize data by numerical attribute)" - sums
up the values from a common numeric attribute shared among in put spatial
datasets that overlap within each grid cell over a spatial extent
• Input Folder or File Geodatabase- Path to a folder or file geodatabase (gdb)
containing spatial data to be included in CSIL analysis. The CSIL tool will search this
input path and all subsequent folders and geodatabasesfor spatial data, including
shapefiles, feature classes, rasters, and feature raster datasets to be included in the
CSIL run.
• Spatial Reference System - (Optional) Projection to build the output CSIL layer in and
re project all spatial data within Input Folder or File Geodatabase into, as CSIL requires
all data to be in the same spatial reference system (SRS). If not provided here and
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data are in differentSRSs, CSIL will request information during runtime as needed. In
addition, if a datum shift (i.e., geographictransformation) is required, the tool will
generate a list of datum shifts for the user to select from while running.
• Start Date - (Optional) If provided, the tool will search data for date-formatted
attributes and query. Data with a date field will then be filtered starting with the date
provided. If datasets have no attribute table, or no date field, they are assumed
atemporal and will be included in subsequent processing steps.
• End Date - (Optional) If provided, the tool will search data for date-formatted
attributes and query. Data with a date field will then be filtered ending with the date
provided. If a Start Date is provided, but no End Date, data with date attributes will
be queried to only exact matches of the Start Date instead of a date range. If datasets
have no attribute table, or no date field, they are assumed atemporal and will be
included in subsequent processing steps.
• Output CSIL-Output path and file name for output CSIL layer, which is currently set
into a shapefile format.
• Output Extent - (Optional) Vector polygon layer (feature class or shapefile)
representingthe spatial extent of the outputCSILto be created. Note that this will be
re projected into the SRS as needed. If not provided, the tool will derive this area from
the inputdata, based on the largest spatial extentfound.
• OutputGrid Cell Size - (Optional) Cell size (units-squared) of each grid cell of the
output CSIL layer, spanning the Output Extent. Units of which are based on the linear
units in the SRS. If not provided, the tool will calculate using ESRI's default approach.
Model Output
CSIL outputs a multivariate vector grid (polygon shapefile) that contains afield
representing each input dataset, each category, and a total column. Categories are based
on each dataset's parent folder or feature dataset if applicable. The total column is
calculated as the sum of all datasets per grid cell. This value is calculated based on the
selected CSIL analysis.
In addition, a CSVdataset is produced as a field dictionaryto map the fields in the output
CSIL layer's attribute table to the in put datasets and categories.
Risks Behavior
Considered
Originally designed to understand the socio-economic and environmental impacts of oil
spills following Deepwater Horizon, CSIL converts disparate spatial data into useful
information. CSIL has been applied to model potential leakage risk, environmental risk,
socio-economic impact, and induced seismicity. Based on the need and data provided,
CSIL provides a multivariate vector grid to visualize data density, which could represent
area vulnerability or risk presence.
Relevant
Permitting Phase
During the Class VI permitting process CSIL could be applied at multiple steps throughout
the process. It could be applied as an exploratory tool to screen sites for risk and
opportunity. Applying spatial layers representing features pertinent for site
characterization, CSIL could be used to map areas more optimally based on cost or
infrastructure availability. Moreover, CSIL could be applied post-injection to visualize
potential external risks, as an example.
Class VI Permit
Element
Addressed
Site Screening, Area of Review and Corrective Action Plan, Post-Injection Site Care and
Site Closure Plan
How the Tool is
Used
CSIL has been used as an exploratoryand analysis toolfora variety of applications. These
applications include summarizing potential socio-economicand environmental impacts to
oil spills, providing a spatial analysis of anthropogenic and natural factors related to
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induced seismicity, visualizing potential leakage pathways, quantifying spatial uncertainty
for geologic mapping, and mapping global oil and gas infrastructure.
Last Updated
Latest desktop release, October2020
Latestonline release,July2021
Ongoing
Development
Yes, currently working on a stand-alone desktop version of the tool, not reliant on ArcGIS
software. The tool has an active user community and sup port for this tool is available.
Ease of Use
The desktop version of the CSIL tool is currently accessible through EDX and GitHub as an
ArcGIS Toolbox complete with a user interface and help documentation. CSIL can be
down loaded and ran through ArcGIS as an add-in toolbox. Users might need to run a
dependency installer prior to use, based on their version of ArcGIS, but that is a simple
double-clickon an installerfile.
Users do not need any computer programming skills to use the tool, but they should
understand the in put spatial data the feed into the tool. The tool is built for GIS and non-
GIS users alike and runs critical pre processing checks and steps as needed (including
putting all data into a common spatial reference system).
The online versions of the CSIL tool are currently available through common operating
platforms, which have limited user access. The online CSIL tools have a user interface and
assist with documentation, but they are limited to the spatial area they run on and have
been tailored for specific uses. These uses include quantifying potential impacts of
offshore oil spills or summarizingdatafor National Environmental PolicyAct analyses.
All versions of the CSIL tool have been written in the widely used Python programming
language. The desktop version requires access to the arcpy module (ArcGIS required),
whereas online and the in-development stand alone desktop versions apply open-source
modules includinggdal.
Computational
Speed
The computational speed of CSIL depends on several factors: desktop versus online
version, amountof inputdata, how preprocessed the inputdata is (i.e., is it all in the same
spatial reference system or does it need to be projected), the area of the extent being
analyzed, and the grid cell size.
Computational speed for the desktop tool is discussed in the 2019 paper, Cumulative
spatial impact layers: A novel multivariate spatio-temporal analytical summarization tool,
where speedsrangefrom 1 second to over40 minutes, substantially fasterthan
processingdata usingthe same method manually.
Tool Verification
Asa data-driven tool, results from CSIL areas accurate as the inputdata provided by the
user. Moreover, users inputthe spatial extentand gridcell size into this multi-scale tool,
so the spatial accuracy is based on user in put.
Related
References
Websites:
Desktop tool on EDX tool - httDs://edx.netl.doe.eov/dataset/cumulative-SDatial-imDact-
lavers
Online version of tools on Common OperatingPlatformsbuiltfor NETL, Bureau of Safety
and Environmental Enforcement (BSEE), and Bureau of Ocean Energy Management
(BOEM) (limitedaccess) - httDs://edx.netl.doe.eov/coD/
Offshore Risk Modeling Suite - httDs://edx.netl.doe.eov/offshore/Dortfolio-items/risk-
modeline-suite/
Tool publication:
Romeo, L.; Nelson, J.; Wingo, P.; Bauer, J.; Justman, D.; Rose, K. Cumulative spatial impact
layers: A novel multivariate spatio-temporal analytical summarization tool.
Transactions in GIS 2019.
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Original method discussed in publications:
Bauer, J. R.; Nelson, J.; Romeo, L.; Eynard, J.; Sim, L.; Halama, J.; Rose, K.; Graham, J.A
Spatio-Temporal Approach to Analyze Broad Risks and Potential Impacts
Associated with Uncontrolled Hydrocarbon Release Events in the Offshore Gulf Of
Mexico; NETL-TRS-2-2015; EPActTechnical Re port Series; U.S. Departmentof
Energy, National EnergyTechnology Laboratory: Morgantown, WV, 2015;p 60.
https://edx.netl.doe.gov/dataset/a-spatio-temporal-approach-to-analvze-broad-
risks-potential-impacts
Romeo, L.; Bauer, J. R.; Rose, K.; Disenhof, C.; Sim, L.; Nelson, J.; Thimmisetty, C.; Mark-
Moser, M.; Barkhurst, A. Adapting the National EnergyTechnology Laboratory's
Offshore Hydrocarbon Integrated Risk Assessment Modeling Approach forthe
Offshore Arctic; NETL-TRS-3-2015; EPActTechnical Report Series; U.S.
Departmentof Energy, National EnergyTechnology Laboratory: Morgantown,
WV, 2015; p 40. https://edx.netl.doe.gov/dataset/adapting-the-netl-offshore-
integrated-assessment-modeling-app roach
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A.5 GEOSTATISTICAL ANALYSIS
Predictions of the spatial extent of sub surface formations and features typically requires the
geostatistical interpolation of sparce data. Tools in this category are designed to perform these
geostatistical calculations.
A.5.1 Stanford Geostatistical Modeling Software (SGeMs)
Tool Name
SGeMs
Developer/Owner
Stanford/open-source
Tool Type
Geostatistical Analysis
Description
Open-source computer package for solving problems involving spatially related variables.
It providesgeostatisticspractitionerswith a user-friend lyinterface, an interactive3D
visualization, and a wide selection of algorithms.
Tool Licensingand
Access
0 De n-sou reed own load: httD://see ms.sourceforee.net/
Model Input
Geotechnical information, GIS data, map surfaces
Model Output
Maps, statistics
Risks Behavior
Considered
Geostatistical analysis of geotechnical parameters and distribution, leakage
Relevant
Permitting Phase
Site screening, site characterization
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan
Last Updated
Open-source
Ongoing
Development
Open-source
Related
References
httD://seems.sou rceforee.net/
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A.5.2 Surfer
Tool Name
Surfer
Developer/Owner
Golden Software
Tool Type
Geostatistical Analysis
Description
Surfer is a grid-based mapping program that interpolates irregularly spacedXYZ data into
a regularly spaced grid. Data metrics allowyou to map statistical information aboutyour
gridded data, and surface area, projected planararea, and volumetriccalculationscan be
performed quickly in Surfer. The grid files can be edited, combined, filtered, sliced,
queried, and mathematically transformed, and cross-sectional profile scan also be
computed and exported. Grids may also be imported from other sources, such as the
United States Geological Survey(USGS).The grid is used to produce different types of
maps including contour, color relief, and 3 D surface maps among others. Many gridding
and mapping options are available allowing you to produce the map that best represents
your data.
Tool Licensingand
Access
Commercial license: httDs://www.eoldensoftware.com/Droducts/surfer
Model Input
Geotechnical information
Model Output
Maps, gridded data, surfaces, trend analysis
Risks Behavior
Considered
Leakage, storage resource, faults, fractures, boundaries
Relevant
Permitting Phase
Site screening, site characterization
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Re vie wand Corrective Action Plan
Last Updated
Surfer® 21.2.192 (64-bit) Jul 6 2021
Ongoing
Development
Commercial, regularupdates
Related
References
httDs://www.eeometrics.com/software/eolden-software-surfer/
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A.6 PROJECT PLANNING
Tools in this category are primarily used to make high-level planning decisions for geologic
carbon storage projects.
A.6.1 Designs for Risk Evaluation and Management (DREAM)
Tool Name
Designs for Risk Evaluation and Management (DREAM)
Developer/Owner
PNNL
Tool Type
Project Planning
Description
DREAM is a Java package that designs optimal combinations of sensors and geophysical
surveys to monitor a reservoir or aquifer where some riskof potential contaminant
leakage is expected.
Tool Licensingand
Access
The DREAMv2 tool is publicly available under an open-source license, with a Java
reDositorvavailableat: httDs://eithub.com/Dnnl/DREAM V2
The DREAMv3 tool is currently available on a more limited basis foralpha testing.
Model Input
DREAM requires an ensemble of reservoir injection oraquifer leakage simulationswith
forecasts of the monitored properties (i.e., pressure, C02 saturation, salinity, stress/strain)
as a function of space and time. These can be standard text output files from a multiphase
flow simulator like NU FT or STOMP, or in the form of aTECPLOT or HDF5 file. If the
monitoring design objective is plumeand pressure front tracking, then reservoirC02
injection simulations are required. If the objective is groundwaterqualitymonitoring,
then aquifer brine and CO2 leakage simulations are needed as input.
Model Output
DREAM outputs a set of proposed monitoring plans graphically within the user interface,
and also produces a comma-delimited text file which the user can use to perform their
own further analyses.
Risks Behavior
Considered
DREAM was designed to helpminimize theriskof unintended migration of C02or brine
through a legacy we llbore or a fracture in the caprock. There is no practical reason one
could not use it to monitor for other types of groundwater risk cases such as nuclear
waste storage sites, coal ash ponds, landfills, or concentrated livestock feeding
operations.
Relevant
Permitting Phase
Class VI site characterizationand injection, operations monitoring, post-injection site care.
Class VI Permit
Element
Addressed
Site Characterization, Testing and Monitoring Plan, Post-lnjectionSite Care and Site
Closure Plan
How the Tool is
Used
The user would assemble their setof input files eitherby runningtheir own STOMP or
NUFT simulations, or by running any other reservoir or leakage simulation they choose,
including NRAP-Open-IAM, and usingthe provided Python scripts to convert the outputs
to HDF5 format.
They would then run the DREAM executable (a JAR file) and use the GUI to select the
directory where the inputs are stored. They would then respond to a series of prompts
from the GUI, clarifying information about the types of sensors available such as their cost
and their sensitivity to the monitored parameter, such as pressure or CO 2 saturation. The
user would also specify wherein the field monitoring sensors are and are not feasible to
deploy (for example due to topography, land access, logistical constraints), and would
define which optimization algorithm they would like DREAM to use.
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DREAM then runs the given optimization and provides a set of ideal monitoring plans
tailored to the particularsite.
Last Updated
The DREAMv2 GitHub release was last updated June 8,2020. The DREAMv3 repository is
still beingactivelydeveloped, and was last updated October 15,2021.
Ongoing
Development
DREAMv3 is under active development and is in the process of alpha testing, and support
from the developmentteam is available.
Ease of Use
The GUI version hasfewerfeaturesbuthasa user's manual with examples and a
description of how to choose inputs and use outputs. The user would need some level of
familiarity with geology and geomechanics but not expert-level knowledge. The GitHub
Python library has documentation and examples but requires a basic level of familiarity
with Python.
Computational
Speed
The optimization is highly de pendent on the size of the in put files, and the complexity of
the monitoring site. Some smaller runs complete on the order of less than a second, while
large complexsites can run for several days.
Tool Verification
A set of unit and integration tests have been developed forQA/QC purposes.
While a benchmark solution is not gene rally available for the more complex optimization
problems that DREAM is developed for, the optimization algorithms have been tested
against Monte Carlo and Grid Search methods and perform much more efficiently.
Related
References
Bacon, D. H.; Yonkofski, C. M.; Brown, C. F.; Demirkanli, D. 1.; Whiting, J. M. Risk-based
post injection site care and monitoring for commercial-scale carbon storage:
Reevaluationof the FutureGen 2.0site using NRAP-Open-IAM and
DREAM. International Journal of Greenhouse Gas Control 2019,90,102784.
Huerta, N.; Bacon, D.; Carman, C.; Brown, C. F. NRAP Toolkit Screening for CarbonSAFE
lllinois-Macon County; No. DOE-UIUC-29381; Univ. of Illinois at Urbana-
Champaign, IL (United States); Illinois State Geological Survey, 2020.
Vasylkivska,V.; Dilmore, R.; Lackey, G.; Zhang, Y.; King, S.; Bacon, D.; Chen, B.; Mansoor,
K.; Harp, D. NRAP-Open-IAM: A Flexible Open-Source Integrated-Assessment-
Modelfor Geologic Carbon Storage Risk Assessment and
Management. Environmental Modelling & Software 2021,143,105114.
Yonkofski,C. M.; Davidson,C. L.; Rodriguez, L. R.; Porter, E. A.; Bender,S. R.; Brown, C. F.
Optimized, budget-constrained monitoring well placement using DREAM. Energy
Procedia 2017,114,3649-3655.
Yonkofski,C. M.; Gastelum,J. A.; Porter, E. A.; Rodriguez, L. R.; Bacon, D. H.; Brown,C. F.
An optimization approach to design monitoring schemes for CO 2 leakage
detection. International Journalof Greenhouse Gas Control 2016,47,233-239.
Yonkofski, C.; Tartakovsky, G.; Huerta, N.; Wentworth, A. Risk-based monitoring designs
for detecting C02 leakage through abandonedwellbores: An application of
NRAP's WLAT and DREAMtools. International Journal of Greenhouse Gas Control
2019,91,102807.
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A.6.2 FE/NETL Carbon Storage Cost Model
Tool Name
FE/NETL CC>2Saline Storage Cost Model
Developer/Owner
NETL
Tool Type
Project Planning
Description
The C02 Storage Cost Model is an Excel®-based tool that estimates the first-year break-
even price to store a tonne ofC02inadeep saline aquifer. The model has four interactive
modules that serve as its foundation: Project Management, Financial, Geologic, and
Activity Cost. The C02 Storage Cost Model incorporates the labor, equipment, technology,
and financial instruments needed to be in compliance with U.S. EPA Underground
Injection Control (UIC) Class VI regulations and Subpart RRof the Green house Gas
Reporting Rule.The purposeof this modelisto mimic C02storage operationsto estimate
the costs (e.g., capital, ope rating, financing, and revenue) associated with a potential C02
saline storage project; this model is not reservoir modeling software. Default parameters
within the model are basedon EPA'seconomicanalysisoftheirClassVI regulations.These
parameters include the storage project timeline—a C02 storage project has 30 years of
injection operations followed by 50 years of PISC and site closure with up-frontyearsfor
site selection, characterization, permitting, and construction reflectinga base case
scenario.
Tool Licensingand
Access
Open-Source. Can be downloaded from:
httDs://edx.netl.doe.eov/dataset/fe-netl-co2-saline-storaee-cost-model-2017
Model Input
• Key_lnputs. Key management decisions are entered in this tab including annual
volume of C02 injected, years of injection, time span for other stages of a storage
project, some two dimensional (2-D)and threedimensional (3-D) seismic parameters,
well spacingfor monitoringwells,and financial parameters defining the business
scenario to be modeled.
• Financial Responsibility Inputs. This tab contains modeler in puts for the Financial
Responsibility(FR) instrumentincludingthe selection ofthe instrumentand financial
parameters for each instrument. The "Fin_Resp_lnputs" worksheet also includes
output information pertaining to the costs of all components and instruments of FR
with the results ofthe single formation being displayed in this tab. A multiple
formation evaluationwill display results forthe last formation evaluated.
• Activity_l nputs. This worksheet contains tables of modeler inputs that define costs of
parameters related to the project. These items are divided intofourtable groups: (1)
Parameters Consistent Across all Activities, (2) Activity-Specific Parameters, (3)
Parameters Used in Activities across Multiple Stages, and (4) Well-Drilling Costs.
• Surface Equipment Cost. Capital costs and annual operation and maintenance (O&M)
costs for surface equipment/facility at a saline storage site are specified in this
worksheet. Surface equipment includes a feeder pipeline; equipment/facility, roads,
and buildings needed to operate the injection wells;and equipmentand roads
related to storage field operations.
• Back-End Cost Items.This worksheetenables the modeler to fully auditand review
the model calculations. It calculates the appropriate annual cost for each activity
utilized in a storage project and posts this cost in the year(s) it is incurred.
• Drilling Costs. This worksheet performs the calculations of drilling costs.
• Geologic Module. This module includes the geologic database, storage coefficients,
and geo-engineering equations and calculates C02injectivity, n umber of C02 injection
wells, and C02 plume area; the latter two are fundamental cost drivers for any C02
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storage project. It also calculates waterwithdrawal (production) from the C02storage
reservoir as well as subsequent treatment and disposal (injection) of water not
rendered potable.
Model Output
• Summary Output. A summary of many important outputs of the model is within this
tab. This worksheet also includes output information from the Project Management,
Geologic, and Financial modules with the results of a single formation being displayed
in this tab. A multiple formation evaluation will display re suits for the last formation
evaluated.
• Cost Breakdown. This tab uses data throughout the model to sum costs across
different categories.Thesesumsareused in someofthe outputthe model produces.
Risks Behavior
Considered
Financial Risks
Relevant
Permitting Phase
Site Screening, Site Characterization, Injection Operations, Post-Injection Closure
Class VI Permit
Element
Addressed
Site Screening, Financial Assurance Demonstration, Well Construction Details
How the Tool is
Used
The purpose of this model is to mimic C02 storage operations to estimate the costs
associated with a potential C02 saline storage project; this model is not reservoir
modeling software. The Storage Cost Model providesa flexible way to allow users to tailor
the model to fit the requirements of each individual project by adjusting parameters in
each stage (e.g.,financial parametersor project lifetime). The storage projectcosts
estimated by the model occurin oneor moreofthe five stagesof a storage project: site
screening, site selection and site characterization, permitting and construction,
operations, and PISCand site closure.
Last Updated
September2017
Ongoing
Development
Yes
Ease of Use
FE/NETL C02Saline Storage Cost Model is developed in Excel with customized Visual Basic
for Applications (VBA) programming language to extend its functionality. Users with
Microsoft Excel and computer programmingexperiencecan access the complete
functionality of the model. A customized ribbon is also available for users to run the
model.
Computational
Speed
A single formation calculation takes seconds to determine the C02 price making the Net
PresentValue (NPV) zero.
Tool Verification
The details of the model can be found here: httDs://www.netl.doe.eov/enerev-
analvsis/details?id=2404
Related
References
NETL. FE/NETL C02Saline Storage Cost Model; U.S. Department of Energy, National
Energy Technology Laboratory. Last Update: Sep 2017 (Version 3).
httDs://www.netl.doe.eov/research/enerev-analvsis/search-
Dublications/vuedetails?id=2403
Grant, T.; Morgan, D. FE/NETL CO 2 Saline Storage Cost Model; User's Manual; 2017.
httDs://www.osti.eov/servlets/Durl/1557137
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A.6.3 SimCCS
Tool Name
SimCCS: Open-source software for designing CO2 capture, transport, and storage
infrastructure
Developer/Owner
Carbon Solutions, LLC.
Tool Type
Project Planning
Description
SimCCS is an open-source software developed to assist industry and governments in
making CCS infrastructure decisions. The software accesses public- or user-provided CO2
source, sink, and transportation data to create and solve an optimization problem to
determine the most cost-effective CCS infrastructure design (e.g., minimizing costs or
maximizing profits). The optimization problem is solved via a third-party optimization
engine (e.g., C-Plexor Gurobi) on a local desktop computing platform. Users of SimCCS
have the flexibility to adjust designs for changes in tax credits, CO 2 price, and address
uncertainties associated with emission rates at sources and injection rates and capacities
at sinks.
Tool Licensingand
Access
SimCCS software isa proprietarysoftware available through CarbonSolutions, LLC.
httDs://www.carbonsolu tionsllc.com/software /simccs/
Model Input
SimCCS addresses all parts of the CCS sup ply chain to find cost savings, revenue streams,
and risks via three submodules:the optimization engine,the CostSurface Multi-Layer
Aggregation Program (CostMAP),and the Sequestration of CO2T00I (SCO2Tor "Scott").
The optimization engine brings together input data from the user, CostMAP, and SC02Tto
model an end-to-end CCS supply chain that accounts for CO 2 capture, CO2 pipeline
transport, and C02Storage.
• Capture data: The capture data includes parameters for each source location,
including an ID, name, latitude/longitude location, fixed opening cost, variable
ope rating cost, per unit capture cost, and a maximum CO 2 production rate.
• Storaee data: The storaee data includes parameters for each storaee location,
including a label, latitude/longitude location,fixedopeningcostfor the entire
location, variable operatingcost for the entire location, fixed opening and variable
operatingcostsforeach well, injection cost, and a maximum capacity for each well
and for the entire location.
• Transport data: We iehted-cost surface data generated from CostMAP are used to
determine the cost of building pipeline networks. Developing the weighted-cost
surface involves laying a grid overthe modeled domain and determining the cost of
traversing from one cell to another. Traversing from cell-to-cell is a function of
underlying topography (slope and aspect), land ownership (lOdefaultclasses), land
use (16 default types), crossings (rail, river, and roads), existing pipeline rights-of-way
(ROWs), and population density. These inputs are provided in SimCCSor users can
use their own GIS raster files.
Model Output
Outputs from SimCCS include intermediate outputs (the pipeline candidate network and
MPS file) and final solutions (SOL File and GIS shapefiles).
• Candidate network: Unlike eeoeraphicallvfixed capture and storaee facilities. CCS
pipeline networks need to be modeled, since they do not yet exist in most areas. An
intermediate output called the candidate pipeline is outputted as a GIS-shapefile
from the SimCCS optimization engine based upon the weighted-cost surface
generated in CostMAP. The candidate networkis a subgraph of all possible pipeline
routes between capture and storage facilities, calculated usingshortest-path
algorithms.
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• MPS file: Oncesourceand storaee locations are parameterized and acandidate
pipeline network has been identified, the user is able to start formulating
infrastructure design optimization problems. This formulation takes the form of
mixed-integer linear programing (MIP) problem that is stored for the user in a
Mathematical ProerammineSvstem (MPS)file.
• SOL file and GIS shape files: The SO Lfile contains solutions on which source and
storage locations were opened, how much CO 2 was captured and stored, and where
to purchase various sized pipelines. This information is visualized in the GUI. Costs are
broken down by capture, transport, and storage and are also displayed for
comparison purposes. SimCCS also ge ne rates G IS Shapefiles of this information,
includingsource locations, storage locations, pipeline routes, and C02flows.
Risks Behavior
Considered
SimCCS does not explicitly consider risk but does allow users to avoid building pipelines in
areas of their choosing (e.g., environmentally or socially sensitive areas).
Relevant
Permitting Phase
Site Screening, Site Characterization, Injection Operations, Post-Injection Closure
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan
How the Tool is
Used
SimCCS generates end-to-end CCS infrastructure solutions through a four-step workflow
that can be characterized as inputs, problem creation, problem solving, and analysis.
SimCCS in puts CO2 capture, transport, and storage data to construct the MIP problem.
The problem is solved and outputs can be analyzed in the SimCCS GUI or brought into
third-part software, like a GIS, for further analysis.
Last Updated
August2021
Ongoing
Development
Yes
Ease of Use
SimCCS runs on any Java-enabled machine and requires no dependencies beyond what is
packaged with the codeto create the MIP. However, users do needan optimization solver
on their local machineto solve the MIP.
Computational
Speed
The computational costs of solving MIP problems can vary widely depending on the
number of parameters. In SimCCS most solutions are solved quickly. However, as the size
of the geography increases and the number of sources/sinks increase, computational
efficiency declines. SimCCS developers are actively developing heuristics to improve
efficiency.
Tool Verification
Components of SimCCS have been verified via various scientific papers (some listed
below).
Related
References
httDs://www.carbonsolu tionsllc.com/
Hoover, B.; Yaw,S.; Middleton, R. CostMAP:an open-source software package for
developing cost surfaces using a multi-scale search kernel. International Journal
of Geographical Information Science 2020,34,520-538.
Middleton, R. S.; Chen, B.; Harp, D. R.; Kammer, R. M.; Ogland-Hand, J. D.; Bielicki, J. M.;
Clarens, A. F.; Currier, R. P.; Ellett, K. M.; Hoover, B. A.; McFarlane, D. N. Great
SC02T! Rapid tool for carbon sequestration science, engineering, and
economics. Applied Computing andGeosciences 2020, 7,100035.
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Middleton, R. S.; Yaw,S. P.; Hoover, B. A.; Ellett, K. M.SimCCS: An open-source tool for
optimizing CO2 capture, transport, and storage infrastructure. Environmental
Modelling & Software 2020,124,104560.
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A.7 RELEASE, TRANSPORT, AND RECEPTOR RESPONSE
Fate and transport modeling of C02 and brine through leakage pathways and into sensitive
receptors is required to characterize the leakage risks at a GCS site. Tools in this category are
primarily used to model CO2 and brine leakage through leakage pathways and/or into potential
receptors (e.g., shallow aquifers).
A.7.1 MODFLOW with MT3DMS/RT3D
Tool Name
Modular Three-Dimensional Finite-Difference Groundwater Flow Model (MODFLOW) with
Multispecies Mass Transport in 3-Dimensions (MT3DMS) or Reactive Transport in 3-
Dimensions (RT3D)
Developer/Owner
United States Geological Survey
Tool Type
Release,Transport,and Receptor Response
Description
A wide ly-used ground water flow simulation tool that can simulate three-dimensional (3D)
transport of a multiple solute species in flowing groundwater. Originallydeveloped and
released solelyas a groundwater-flow simulation code when first published in 1984,
MODFLOW's modular structure has provided a robust framework for integration of
additional simulation capabilities that build on and enhance its original scope. The family
of MODFLOW-related programs now includes capabilities to simulate coupled
groundwater/surface-water systems, solute transport, variable-density flow (including
saltwater), aquifer-system compaction and land subsidence, parameter estimation, and
groundwater management.
Tool Licensingand
Access
Open-source code can be freely downloaded here:
httDs://www.uses.eov/software/modflow-6-uses-modular-hvdroloeic-model with no
license needed.
Model Input
Initial concentration of solute species, hydrological parameters such as hydraulic head,
hydraulic conductivity (kx, ky, and kz), transmissivity, storage coefficient, residual
saturation, etc.
Model Output
Hydraulic head distribution (MODFLOW)and concentration distribution(s)
(MT3DMS/RT3D) on a 3D grid
Risks Behavior
Considered
Environmental risk to groundwater and surface water
Relevant
Permitting Phase
PrimarilySite characterization and in some instances, groundwater monitoringduring
injection
Class VI Permit
Element
Addressed
Site Characterization, Testingand Monitoring Plan
How the Tool is
Used
The tool would be used to predict where leaks might manifest in groundwaterand how
they might be attenuated through groundwater flow. It would inform the level of risk to
groundwaterand where monitoring of groundwatershould be most implemented.
Last Updated
The cur rent version of MODFLOW 6 is version 6.2.2, re leased July 30,2021.
Ongoing
Development
The USGS Water Mission Area actively develops and supports the MODFLOW suite of
programs. Ongoing efforts include providingmaintenanceand support for existing
versionsof MODFLOWsuchas MODFLOW6, MODFLOW-2005, MODFLOW-NWT,
MODFLOW-USG, MODPATH, MT3D-USGS, and related and supporting programs such as
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FloPy and PEST++. Cur rent development efforts are focused on adding new capabilities to
MO DFLOW 6. These development efforts include:
• A Basic Model Interface (BMI) for MODFLOW6 to supporteasiercouplingwith other
models such as those that simulate groundwater recharge, geochemical mixing, and
optimization and management, as well as mode Is that would benefit from tight
coupling.
• A Grou nd water Transport (GWT) Model that works with structured or unstructured
grids, the Newton formulation, and the advanced stress packages available in
MODFLOW6.
• A new Buoyancy (BUY) Package that extends the Groundwater Flow (GWF) Model of
MO DFLOW 6 to re present variable-density ground water flow. This new BUY Package
makes it possible to simulate problems related to saltwater intrusion, deep-well
injection, aquifer storage and recovery, and brine migration.
• Extension of MODPATH to track particles in MO DFLOW 6 models that use
Discretization by Vertices (DISV) and fully unstructured (DISU) grids.
• Parallelization of the MODFLOW 6 multi-model framework for High-Performance
Computing (HPC) using the Message Passing Interface (MPI). Preliminary versions of
MO DFLOW 6 with this new capability have been used to solve groundwater models
with billions of model cells. This new parallelization capability is being developed in a
general manner that can be easily extended for future MO DFLOW model types (for
example GWT); applied at local, regional, and continental scales; and can be used on
desktops and HPC systems.
In addition to these ongoing efforts, future efforts may include development of new
surface water, pipe network, and heat transport models. The USGS plans to continue
these development efforts to meetthe needs of the USGS, our stakeholders, and the
needsofthe hydrologic modelingcommunity. Users are encouraged to track MODFLOW
develoDmentsthroueh our version-controlled MO DFLOW 6 reDositorv.
Ease of Use
MODFLOWisacommand line executable program written in FORTRANthat reads ASCII
text and binary input files and writes ASCII text and binary output files. Although
experienced MODFLOWusers may be able to create MODFLOW inputfiles by hand, most
MODFLOWusers rely on a graphical user interfaceto prepare the inputfilesand post-
process the outputfiles. The MO DFLOW program itself does notgeneratecontourplotsor
any other type of graphical output. These plots must be generated from MODFLOW
results using other software programs. The USGS distributes several free pre- and post-
processors for MODFLOW. Commercial GUIs are also availablefor sale by private vendors.
Successful use of MODFLOWtypically requires a college-level modeling course or
professional training on ground water mode ling. In some situations, the USGS can provide
training to governmental agencies with a cooperative agreement with the USGS; agencies
can con tact their cooperating USGS office for additional information. MO DFLOW courses
are also offered by several private companies.
Computational
Speed
The model is gene rally designed for computational efficiency. Speeds are not limited in
anyway. It gene rally runs with in minutes.
Tool Verification
httDs://www.eDa.eov/sites/default/files/2015-05/documents/Draft-Risk-Modeline-
Re Dort-ADDendix-A-SeDtember-11-2013.Ddf
httDs://www.wiDD.enerev.eov/librarv/cra/CRA-
2014/References/Others/US EPA 2006 TSD for Section 194 23 Models and ComDut
er Codes.Ddf
Related
References
httDs://www.uses.eov/mission-areas/wate r-re sources/science/modflow-and-related-
Droerams?at-science center obiects=0#at-science center obiects
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A.7.2 Semi-Analytical Leakage Solutions for Aquifers (SALSA)
Tool Name
SALSA (Semi-Analytical Leakage Solutions for Aquifers)
Developer/Owner
Abdullah Cihan/LBNL
Tool Type
Release, Transport, and Receptor Response
Description
SALSA computes pressure or head in aquifers and aquitards, leakage rates and cumulative
leakages through abandoned we lis for multilayered aquifer systems with multiple
injection, pumping and leakywells. Injection and extraction rates can change with time,
and initially the systemcan be hydrostatic, overpressu red, or underpressured.
Tool Licensingand
Access
The code is accessible by request through the developerand LBNL.
Abdullah Cihan: httDs://eesa.lbl.eov/Drofiles/abdullah-cihan/
Model Input
Layer-wise properties for aquifers and aquitards such as thicknesses, permeability,
storativity, anisotropy ratioand initial heads. Also, coordinates of the wells, screen levels
for injection and pumping wells with time-dependent injection and extraction rates,
conductivity distribution along the leaky wells with options to identify cased, open and
plugged segments.
Model Output
Time-dependent pressure or head changes in aquifers and aquitards, leakage rates and
cumulative leakages at different aquifer-leaky well interfaces, contour plot for are al
distribution of head or pressure changes in user-selected aquifers
Risks Behavior
Considered
Leakage risk
Relevant
Permitting Phase
Site screening, injection and post-injection pressure behaviorin multilayered systems
Class VI Permit
Element
Addressed
Site Screening, Area of Review and Corrective Action Plan Post-Injection Site Care and
Site Closure Plan
How the Tool is
Used
The tool can be used to estimate pressure front evolution in response to injection in
multi-layered aquifer systems and the leakage risks through leaky paths Leakage rates
and cumulative leakages can be calculated in the presence of leaky abandoned wells,
including leakages due to injection into already overpressu red storage reservoirs.
Last Updated
The tool was last updated in September2021.
Ongoing
Development
The code is ready to use. The code has been used in several different research
institutions, butthere is notan active usercommunity.
Ease of Use
No user interface currently, but the code can be built into NRAP Open-IAMin the future.
The code uses one in put text file and generates output files that can be directly dragged
into the Tecplot software for plotting the results. The users do not need programing skills,
butsome basic knowledge about groundwater hydrology would be needed.
Computational
Speed
The code runs very fast (seconds), because it is a mesh-free semi-analytical model.
Tool Verification
Verified extensively with existinganalyticalsolutionsforsimpler problems and high-
fidelity numerical models. These verificationswere mostly documented in the published
literature.
Related
References
There is a user manual for the code, but it needs to be updated with the recent
developments
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Burton-Kelly, M. E.; Azzolina, N. A.; Connors, K. C.; Peck, W. D.; Nakles, D. V.; Jiang,T. Risk-
based area of review estimation in overpressured reservoirs to support injection
well storage facility permit requirements for CO2 storage projects. Greenhouse
GasSci Technol2021,11, 887-906. https://doi.org/10.1002/ghg.2098
Cihan, A.; Birkholzer, J.; Zhou, Q. Pressure Buildup and Brine Migration during CO2 Storage
in Multilayered Aquifers. Ground Water2012. doi: 10.1111/j.l745-
6584.2012.00972.x
Cihan, A.; Oldenburg, c. M.; Birkholzer, J. Leakage in Abnormally Pressured Multilayered
Aquifer Systems: Solutions Based on Laplace Transform and Matrix Calculus; 2021
under preparation.
Cihan, A.; Zhou, Q.; Birkholzer, J. Analytical Solutions for Pressure Perturbation and Fluid
Leakage through Aquitards and Wells in Multilayered Aquifer Systems. Water
Resources Research 2011. doi:10.1029/2011WR010721.
Cihan, A.; Zhou, Q.; Birkholzer, J. T.; Kraemer, S. R. Flow in horizontally anisotropic
multilayered aquifer systems with leaky wells and aquitards. Water Resources
Research 2013,50. doi:10.1002/2013WR013867.
Oldenburg, C. M.; Cihan, A.; Zhou, Q.; Fairweather, S.; Spangler, L. H. Geologic carbon
sequestration injection wells in overpressured storage reservoirs: estimating area
of review. Greenhouse Gases: Science and Tech no logy 2016.
doi:10.1002/ghg,1607.
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A.7.3 Tfrack
Tool Name
Tfrack
Developer/Owner
Quanlin Zhou (LBNL)
Tool Type
Release, Transport, and Receptor Response
Description
The Tfrack code in MATLAB can analytically predict evolution of fracture length, spacing,
aperture, and pattern of thermal fractures around vertical and h orizontal injection wells
(aswellas hydraulic fractures or faults). Thermal fracturesare inducedand propagated by
significantcoolingand thermal stresscaused by CO2injection through/intodeep hot
formations. They create leakage flow paths in caprock for injected CO2. This type of
leakage risk has been overlooked in the CCS community for site permitting and operation.
Tool Licensingand
Access
The website for free download is under development
Quanlin Zhou: httDs://eesa.lbl.eov/Drofiles/auanlin-zhou/
Model Input
One, two, or three dimensionless model parameters: effective confining stress, wellbore
radius, and horizontal stress ratio are needed for half-plane thermalfracturesfrom a
hydraulic fracture, radial thermal fracturesaround a horizontal well, or longitudinal
thermal fractures around a vertical well, respectively.
Model Output
Fracture length, spacing, aperture, and pattern of half-plane, radial, and longitudinal
thermal fractures, as functions of time for a specific application
Risks Behavior
Considered
A new type of leakage risk caused by CO 2 leakage through longitudinal thermal fractures
out of injection wells in sealing formations; a new risk of reduced storage capacity and
efficie ncy in a th ick storage formation or stacked storage formations caused by focused
C02flowthrough thermal fractures
Relevant
Permitting Phase
Applicable to site screening, site characterization, and injection of a Class VI permit
Class VI Permit
Element
Addressed
Area of Review and Corrective Action Plan, Post-Injection Site Care and Site Closure Plan,
Emergencyand Remedial Response Plan
How the Tool is
Used
In the current Class VI permitting workflow, hydraulic fracturing is avoided by limiting
injection pressure to be less than fracturing pressure (without consideration of cooling-
induced thermal stress). This tool focuses on predictingthermalfractures and related
leakage risks for injection and post-injection periods.
Last Updated
The tool was last updated October 1,2021
Ongoing
Development
The development of the tool is completed, but it does not have an active user community.
Promotion ofthe applications ofthe tool is key to permitting.
Ease of Use
No graphical user interface. The code is in MATLAB, and users can runthe tool as a black
box or use derived type curves without a computer.
Computational
Speed
This tool is a collection of analytical solutions, and iscomputationallyfast.
Tool Verification
The tool has been verified for accuracy by excellent agreements with numerical modeling
results. The verifications we re documented in three related journal publications (see
below):
Related
References
Chen, B.; Zhou, Q. Analytical prediction of thermal fracturing around horizontal wells.
Geophysical Research Letters 2021 (submitted).
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Chen, B.; Zhou, Q. Scaling behavior of thermally driven fractures in deep low-permeability
reservoirs: a plane strain model with 1-D he at conduction. Journal of Geophysical
Research - SolidEarth 2021,126,202DB022964(under revision).
Chen, B.; Zhou, Q. Scaling behavior of thermally driven longitudinal fractures along a
vertical welhaplane strain model with radial heatconduction.Joumo/o/
Geophysical Research -SolidEarth 2021 (submitted).
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A.8 RESERVOIR SIMULATION
Simulating the behavior of the subsurface C02 plume and corresponding pressure response is a
fundamental requirement of the Class VI permitting process. Tools in this category were
designed to simulate the complex physics associated with multiphase flow in porous media.
A.8.1 Aquifer Injection Modeling Toolbox (AIM Toolbox)
Tool Name
AIM Toolbox
Developer/Owner
Developer: Christian Johnson and Inci Demirkanli (PNNL)
Owner: Region8 EPA (Wendy Cheung)/ORD (Rick Wilkins)
Tool Type
Reservoir Simulation
Description
The audience for this we bap plication is permitting authorities or operators who do not
have modeling experience. The Aquifer Injection Modeling Toolbox ("AIM Toolbox")
software is a user-friendly app that provides a collection of analytical solutions suitable for
evaluating the potential extent of the area impacted by subsurface injection operations
with minimal data input. While specificallydesigned to evaluate brine disposaloperations
(e.g., produced water from oil and gas ope rations that would be disposed into UIC Class
IID wells), it can provide a first cut evaluation ofvisualizingtheextentof an injected
plume in a GIS map to assess potential vulnerable areas within the Area of Review. It is
also well suited to apply for an expansion of the Class II aquifer exemption and
demonstrate that an appropriately sized area is exempted such that the CO2 plume and
pressurefrontremainwithin the approved exempted area. The app currentlycontains
five analytical and semi-analyticalsolutions todelineate the areathatcan potentiallybe
impacted by subsurface operations that range from simple volume fill-up, incorporation
of natural hydraulic gradient, and consideration of the density differential between
injectate and formation flu ids. The app also places the plume relative to existing aquifer
exemptions.
Tool Licensingand
Access
The app is licensed forgovernment use only. Initial deployment is at:
httDs://socrates.Dnnl.eov/eDa-rare-aim/index.html
As of April 2022, the app will be available on the EPA Office of Research and Development
website: httDs://www.eDa.eov/sites/default/files/is-scriDts/aim-toolbox/index.html
Model Input
Depending upon the model selected, the input parameters may include: well location,
groundwater direction, natural hydraulic gradient and dispersivity, flow rate, injection
duration, injectate specific gravity, aquifer thickness, porosity, hydraulic conductivity, and
specific storage.
Model Output
The output is both in numeric and visual form.
Risks Behavior
Considered
Siting issues
Relevant
Permitting Phase
Site Screening
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan, Aquifer
Exemption Expansion
How the Tool is
Used
Provides a quick comparison against applicant-submitted mode Is or during pre-
application process, allowingassessmentof potential siting issues. User can also change
input parameter such as project duration.
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Last Updated
Spring2021
Ongoing
Development
The app is completed, however as funding becomes available, there may be additional
development, such as adding a data layer to include injection and production wells from
state and EPA databases.
Ease of Use
The tool hasa graphical user interface and is very simple to use. No programming
knowledge is required.The utility of this app is in the ease of its use.
Computational
Speed
Computational speeds are nearly instantaneous.
Tool Verification
Model verification includes comparison of outputs to known results or re suits from
independent methods. PNNL has developed a robust QA document that can be shared.
Related
References
Additional information can be found at: httDs://www.Dnnl.eov/Droiects/aim-toolbox.
includinguserguide.
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A.8.2 CMGGEM
Tool Name
CMGGEM
Developer/Owner
Computer Modelling Group LTD. (CMG)
Tool Type
Reservoir Simulation
Description
GEM is a reservoir dynamic flow simulator that accounts the equation of state (EOS) for
compositional reservoir modeling. Physical processes that occur during CO 2 storage are
integrated in the simulator.
Tool Licensingand
Access
License purchased from CMG: httDs://www.cmel.ca/eem
Model Input
Static geologic model input, known as reservoirdescription
Reservoirfluids components
Rock-fluid types, known as relative permeability foreach rock type
Reservoir initial conditions, including petrophysical properties, initial reservoir pressure,
and temperature conditions
Numerical settings for accuracy and computational efficiency
Well data and recurrent injection/production data
When incorporating geochemical interactions, aqueous chemical equilibrium, mineral
dissolution, and precipitation reactions from Thermo/Phreeqc/Minteq Geo-Chemistry
database need to be selectedand defined.
Model Output
Simulator generates ,sr3file and text format .outfile
Risks Behavior
Considered
Leakage risk
Relevant
Permitting Phase
Site screening, site characterization, area of review (AOR) evaluation, injection, and post
injection
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan, Injection
Well Plugging Plan, Post-Injection Site Care and Site Closure Plan
How the Tool is
Used
CMG is used to simulate site-specific injection capacity, fluid movement, and pressure
changes. The output is then used to determine CO2 plume and AO
CMG can also be used to evaluate geochemical reactions and their potential impacts on
injectivity.
Last Updated
The latest version is October2020.
Ongoing
Development
Versions are updated periodically. There is no active user community. Support is available.
Ease of Use
The tool has a graphical user interface. Computer-programming skills are not needed. An
understanding of reservoir flu id flow physics and reservoir simulation techniques is
neededto run the tool.
Computational
Speed
GEM isdesigned forcomputation efficiency.Simulation time dependson the size and the
type of the model—typically 8-24 hours. Geochemical models can take a longer time to
complete.
Computational speeds can be limited by availability of sufficient clusters/nodes on the
server.
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Tool Verification
The tool has been used forseveral years throughoutthe oil and gas industry.
Related
References
A list of websites, manuals, and publications that provide additional insight into the tool
include the following:
Resources available on httDs://www.cmel.ca/eem
Class, H.; Ebigbo,A.; Helmig, R.; Dahle, H. K.; Nordbotten, J. M.; Celia, M. A.; Audigane, P.;
Darcis, M.; Ennis-King,J.; Fan, Y.; Flemisch, B.; Gasda,S. E.; Jin, M.; Krug, S.;
Labregere, D.; Naderi Beni, A.; Pawar, R.J.; Sbai,A.; Thomas,S. G.; Trenty, L.;
Wei, L. A benchmark study on problems related to CO 2 storage in geologic
formations. Computational Geosciences 2009,13.
httDs://doi.ore/10.1007/sl0596-009-9146-x
Nghiem, L.; Sammon, P.; Grabenstetter, J.; Ohkuma, H. ModelingCO2storage in aquifers
with a fully-coupledgeochemical EOS compositional simulator; Paper presented
at the SPE/DOE Symposium on Improved Oil Recovery, Tulsa, Oklahoma, April
2 004. h ttDS: //do i .ore/10.2118 /89474-MS
Nghiem, L.; Shrivastava, V. K.; Tran, D.; Kohse, B.; Frederick, H.; Hassam, M.; Yang, C.
Simulation of COzStorage in Saline Aquifers; Paper presented at the SPE/EAGE
Reservoir Characterization and Simulation Conference, Abu Dhabi, UAE, October
2009. httDs://doi.ore/10.2118/125848-MS
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A.8.3 ECLIPSE
Tool Name
ECLIPSE
Developer/Owner
Schlumberger
Tool Type
Reservoir Simulation
Description
The ECLIPSE simulator offers a robust set of numerical solutions for fast and accurate
prediction of dynamic behavior for different reservoirs and development schemes
including blackoil, compositional, thermal finite-volume, and streamline simulation. By
choosing from a wide range of add-on options—such as local grid refinements, coalbed
methane, gas field operations, advanced wells, reservoir coupling, and surface networks-
simulator capabilities can be tailored to meet ones need sand enhance reservoir modeling
capabilities.
Tool Licensingand
Access
Commercial: h ttDs://www. software, sib. com/prod ucts/ecliDse#sectionFu IIWidthTable
Model Input
Geological description, Rock properties like porosity, permeability, mechanical properties,
etc., fluid properties like equation ofstate, viscosity, etc.
Model Output
Pressure, saturation, stress, fracture growth, etc.
Risks Behavior
Considered
Leakage risk
Relevant
Permitting Phase
Site screening, site characterization, Injection and post-injection
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan, Testing
and Monitoring Plan, Injection Well Plugging Plan, Post-Injection Site Care and Site Closure
Plan,Stimulation Program
How the Tool is
Used
The tool can be used to run simulations to determine the extent of the plume. Multiple
simulations can be run by varying uncertain parameters.
Last Updated
2020
Ongoing
Development
Yes
Ease of Use
There is a graphical user interface. Trainingcourses are offered.
Computational
Speed
Computationally expensive
Tool Verification
Yes
Related
References
Archer Daniels Midland CCS1 Class VI Permit Documents:
httDs://www.eDa.eov/sites/default/files/2021-05/documents/adm ccsl attachment b -
aor and ca Dlan - final.Ddf
Archer Daniels Midland CCS2 Class VI Permit Documents httDs://www.eDa.eov/uic/archer-
dan iels-mid land-ccs2-class-vi-Dermit-docu men ts
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A.8.4 EASiTool
Tool Name
EASiTool
Developer/Owner
Seyyed A. Hosseini/The University of Texas at Austin
Tool Type
Reservoir Simulation
Description
Tool is developed in MATLABplatform (comes independentof installing MATLAB) and
uses semi-closed form analytical equations to estimate CO2 saturation and pressure
plume evolution with time.
Tool Licensingand
Access
Free.contactdeveloDer:httDs://www.ise.utexas.edu/researcher/sevved hosseini
Model Input
Model inputs are average formation properties (permeability, porosity, pressure,
temperature, salinity, relative permeability, etc.)
Model Output
Number of injection wells needed to inject givenCC>2Volume, pressure, and saturation
plume. Tool is providing some rough estimates of NPVand formation fracture pressure
as well.
Relevant Permitting
Phase
Site screening
Class VI Permit
Element Addressed
Site Screening, Area of Review and Corrective Action Plan
How the Tool is
Used
This tool uses homogenized formation properties to estimate radial extension of the C02
plume and associated elevated pressure. Model inputs are averageformation properties
(permeability, porosity, pressure, temperature, salinity, relative permeability, etc.)
where model is using advanced analytical solutions for closed and open boundary
condition reservoirs to estimate pressure build up in multi-well injection scenarios. Tool
is capable of providing tornado charts for sensitivity analysis.
Last Updated
2017
Ongoing
Development
No new development, but this tool has a very active user base with lots of feedback
received overyears. However, fundingfrom DOE ended in 2017.
Ease of Use
Very easy, single interface
Computational
Speed
Very fast, in seconds
Tool Verification
Results are comparedwith full-physics simulators and published in peer-reviewed
literature.
Related References
Hosseini,S. A.; Ganjdanesh, R.; Seunghee, K. Enhanced Analytical Simulation Tool
(EASiTool) forC02Storage Capacity Estimation and Uncertainty Quantification;
2018. httDs://doi.ore/10.2172/146332 9
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A.8.5 Finite Element Heat and Mass Transfer Code (FEHM)
Tool Name
Finite Element Heat& MassTransferCode(FEHM)
Developer/Owner
Los Alamos National Laboratory (LANL)
Tool Type
Reservoir Simulation
Description
FEHM is a reservoirsimulatorwith capability to simulate coupled thermal-hydrological-
mechanical-chemical processes that take place in the subsurface during variousenergy and
environmental applications. It has proved to be a valuable asset on a variety of projects of
national interest including: environmental remediation ofthe NevadaTestSite,the LANL
Groundwater Protection Program, geologic CO 2 sequestration, enhanced geothermal
energy (EGS) programs, oil and gas production, nuclearwaste isolation, and arctic
permafrost. Subsurface physics has ranged from single-flu id/single-phase flu id flow when
simulating basin scale groundwater aquifers to complexmulti-fluid/multi-phase fluid flow
that includes phase change with boilingand condensingin applications such as unsaturated
zone surrounding nuclearwaste storage facility or leakage of CO 2/brine through faults or
wellbores. The numerical method used in FEHM is the control volume method (CV) for fluid
flow and heat transfer equations which allows FEHM to exactly enforce energy/mass
conservation; while an option is available to use the finite element (FE) method for
displacement equations to obtain more accurate stress calculations. In addition to these
standard methods, an option to use FE for flow is available, as well as a simple finite
difference scheme.
Tool Licensingand
Access
Open-Source
Available at httDs://eithub.com/lanl/FEHM
Website: httDs://fehm.lanl.eov
Model Input
Site specific reservoir models parameters based on geologic model forthe site
Model Output
Time-de pendent 3D reservoir variables including pressure, saturation, temperature, and in
case of mechanical modelingstressand displacements
Risks Behavior
Considered
Can be used to simulate and predict: 1) time-dependent leakage of CO2 and brine through
wellbores and faults as part of leakage risk assessment, and 2) time-dependent
displacements and stress changes as part of induced seismicity risk assessment
Relevant
Permitting Phase
Site Screening, Site Characterization, Injection Operations, Post-Injection Closure
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan, Testing
and Monitoring Plan, Post-Injection Site Care and Site Closure Plan, Emergency and
Remedial Response Plan
Last Updated
2021
Ongoing
Development
Yes
Related
References
Chen, B.; Harp, D. R.; Lu,Z.; Pawar, R.J. On Reducing Uncertainty in Geologic CO 2
Seq uestration Risk Assessment by Assimilating Monitoring Data. International
Journal of Greenhouse Gas Control 2020,94.
Dempsey, D.; Kelkar, S.; Pawar, R. Passive injection: A strategy for mitigating reservoir
pressurization, induced seismicity and brine migration in geologic CO2 storage.
International Journal of Greenhouse Gas Control 2014,28,96-113.
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Dempsey, D.; Kelkar, S.; Pawar, R.; Keating E. Coblentz, Modeling caprock bending stresses
and their potential for induced seismicity during CO 2 injection. International
Journal of Greenhouse Gas Control 2014,22,223-236.
Harp, D. R.; Pawar, R. J.; Carey, J. W.; Gable, C. W. Reduced order models fortransientC02
and brine leakage along abandoned wellbores from geologic carbon sequestration
reservoirs. International Journal of Greenhouse Gas Control 2016,45,150-162.
Harp, D.; Onishi,T.; Chu,S.; Chen, B.; Pawar, R. Developmentof quantitative metrics of
plu me migration at geologic CO2 storage sites. Greenhouse Gases Science &
Technology2019,0,1-16.
Hyman, J. D.; Jimenez-Martinez, J.; Gable, C.; Stauffer, P.; Pawar, R. Characterizing the
impact of network heterogeneity on the injection of supercritical CO 2 into
fracturedcaprock. Transportin Porous Media 2020,131,9315-955.
Keating, E. H.; Harp, D. R.; Dai,Z.; Pawar, R. J. Reduced order model for assessing C02
impacts in shallow unconfined aquifers. International Journal of Greenhouse Gas
Control 2016,46,187-196.
Singh, M.; Chaudhari, A.; Stauffer, P. H.; Pawar, R.J. Simulation of gravitational instability
and thermo-solutal convection during the dissolution of C02in deep storage
reservoirs, Water Resources Research 2020,56, e2019WR026126.
https://doi.org/10.1029/2019WR026126
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A.8.6 GEOSX
Tool Name
GEOSX
Developer/Owner
Lawrence Livermore National Laboratory,Stanford University and Total
Tool Type
Reservoir Simulation
Description
GEOSX is an open-source, multi-physics simulator. Itenrichesthe physicsused in industrial
simulations, allowing complex fluid flow, thermal, and geomechanical effects to be handled
in a seamless manner. Ithas highly scalablealgorithmsforsolvingthese coupled systems,
and improved workflows for modeling faults, fractures, and complex geologicformations.
Tool Licensingand
Access
GEOSX is open-source and released under an LGPL-v2.1license
httD://www.eeosx.ore/
Model Input
Rock properties like porosity, permeability, mechanical properties, etc.; fluid properties like
equation of state, viscosity, etc.
Model Output
Pressure, saturation, stress, fracture growth, etc.
Risks Behavior
Considered
Leakage risk
Relevant
Permitting Phase
Injection and post-injection
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan, Post
Injection Site Care and Site Closure Plan
How the Tool is
Used
The tool can be used to run simulations to determine the extent of the plume. Multiple
simulations can be run by varying uncertain parameters.
Last Updated
2021
Ongoing
Development
Yes
Ease of Use
No graphical user interface. Some level of proficiency with running codes via command line
is perhaps necessary
Computational
Speed
Run time is dependent on several factors. It is computationally expensive and has to be run
in parallel on multiple cores.
Tool Verification
Different aspects of the software have beenbenchmarked. Details can be found at
httD://www.eeosx.ore/
Related
References
httDs://arxiv.ore/abs/2105.09468
httD://www.eeosx.ore/
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A.8.7 Heat and Salinity Transport (HAST)
Tool Name
Heatand Salinity Transport (HAST)
Developer/Owner
Abdullah Cihan/LBNL
Tool Type
Reservoir Simulation
Description
HAST computes pressure, salinity and temperature changes in subsurface by solving three
coupled nonlinear partial differential equations for pressure, salt mass fraction, and
temperature usingthe Finite Volume method.
Tool Licensingand
Access
The code is accessible through the developerand LBNL
Abdullah Cihan: httDs://eesa.lbl.eov/Drofiles/abdullah-cihan/
Model Input
Model geometry, numerical grid (ID, 2D, and 3D Cartesian, or 2D axisymmetriccylindrical
coordinates), hydrogeological and thermal properties in the domain, and initial and
boundary conditions, provided through a single inputfile
Model Output
Time-dependent pressure, salinity and temperature as both contour data and observation
point data (user-selected). Users can also obtain brine leakage fluxes at any arbitrary
selected points
Risks Behavior
Considered
Brine leakage risk
Relevant
Permitting Phase
Site screening, injection and post-injection
Class VI Permit
Element
Addressed
Site Screening, Area of Review and Corrective Action Plan, Post-injection Site Care and Site
Closure Plan
How the Tool is
Used
The tool can be used to estimate evolution of pressure and brine leakage risks for a wide
range of pressure, salinity, and temperature conditions. Natural attenuation of brine leaking
into USDWs can be simulated accurately.
Last Updated
The tool was last updated in June 2021. The earlier versions of the code did notincludeheat
transport.
Ongoing
Development
The development was mainly completed, but a user manual needs to be developed. There is
noactive user community. The code has been used bygraduate students and postdocs.
Ease of Use
No user interface. The code uses one in put text file and generates output files that can be
directly dragged intoTecplot software for plotting the results. The users do not need
programing skills, butsome basic knowledge aboutheatand mass transport in subsurface
and modelingis needed.
Computational
Speed
The code is partially parallelized and maybe efficientlyused to solve complex3D problems.
It typically runs faster compared to the multiphase simulators, because this is a single-phase
flow model of freshwaterand saltwater mixing.
Tool Verification
Verified with analytical solutions, other numerical models and laboratory data. Some of
these verifications were documented in the published literature.
Related
References
There is currently no published user manual for the code.
The following references include either descriptions or applications of the code:
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Agartan, E.; Cihan, A.; Illangasekare, T. H.; Birkholzer, J. T.; Zhou,Q. Mixing and Trapping of
Dissolved CC>2in Deep Geologic Formations with Shale Layers. Advances in Water
Resources 2017,105,67-81.
Cihan, A.; Oldenburg, C. M.; Birkholzer, J. Leakage in Abnormally Pressured Multilayered
Aquifer Systems: Solutions Basedon Laplace Transform and Matrix Calculus; 2021
under preparation. (Presents model comparisonsof the codes HAST and SALSA
with each other)
Cihan, A.; Petrusak, R.; Bhuvankar, P.; Birkholzer, J. T.; Alumbaugh, D.; Trautz, R.
Permeability decline by clayfine migration around a low-salinity fluid injection well.
Groundwater 2021. https://doi.org/10.llll/ewat.13127
Siirila-Woodburn, E. R.; Cihan, A.; Birkholzer,J.T. A risk map methodology to assess the
spatial and temporal distribution of leakage into groundwater from Geologic
Carbon Storage. International Journal of Greenhouse Gas Control 2017,59,99-109.
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A.8.8 MATLAB Reservoir Simulation Tool (MRST)
Tool Name
MATLAB ReservoirSimulationTool (MRST)
Developer/Owner
SINTEF Digital
Tool Type
Reservoir Simulation
Description
MRST is not primarily a simulator, but it is developed as a research tool for rapid
prototyping and demonstration of new simulation methods and modeling concepts. The
toolbox offers a wide range of data structures and computational methods you can easily
combine to make yourown custom-made modellingand simulation tools. MRST offers
comprehensive black-oil and compositional reservoirsimulators capable of simulating
industry-standard models and also containsgraphical user interfaces for post-processing
simulation results.
The software is organized into:
• A minimal core module offering basic data structures and functionality
• A large set of add-on modules offering discretizations, solvers, physical models, and a
wide variety of simulators and workflow tools
The modules contain many tutorial examples that explain and showcase how MRST can be
used to make gene ral or fit-for-purpose simulators and workflow tools. Using MATLAB for
reservoir simulation may seem strange at first, but most of the tools and simulators are
quite efficient and can be applied to surprisingly large and complex mode Is (several real
datasetsare suppliedwith the software). For more computationallychallengingcases, the
open-source OPM Flow simulatorfrom the Open Porous Media initiative is recommended.
Tool Licensingand
Access
Open-source, can be used with MATLABand Octave.
httDs://www.sintef.no/Drojectweb/mrst/
Model Input
Dependenton the MRSTmoduleused.
Model Output
Dependenton the MRST moduleused.
Risks Behavior
Considered
Leakage risk, environmental risk
Relevant
Permitting Phase
Site screening, site characterization, injection, post-injection
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan, Testing and
Monitoring Plan, Post InjectionSite Care and Site Closure Plan
How the Tool is
Used
MRST is, as the name implies, a toolbox that contains many of the features associated with
reservoir simulators such as visualization, solvers, and grid processing/generation, but it is
not a stand-alone/black-box simulator. It assumes that the user is comfortable working
"under the hood" and knows how to choose the right tools for the right job. For running an
Eclipse-type inputfile directly, reviewthe "simulateSPEl" example under ad-blackoilfor a
minimal workingexample.
Last Updated
September 13,2021
Ongoing
Development
MRST is still under development and new versions are published twice a year.
Ease of Use
The tool requires knowledge of the MATLAB/Octave programming language to run.
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Computational
Speed
MRSTis notoptimized for speed.
Tool Verification
httDs://www.sintef.no/Droiectweb/mrst/docu mentation/
Related
References
httDs://www.sintef.no/Droiectweb/mrst/down load/
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A.8.9 Nexus
Tool Name
Nexus
Developer/Owner
Landmark
Tool Type
Reservoir simulation
Description
Software suite for reservoirsimulation equips reservoirengineers with the integrated
modeling capabilities needed to assess, validate, plan, and execute asset development
optimization.
Tool Licensingand
Access
Commercial license: httDs://www.landmark.solutions/Nexus-Reservoir-Simulation
Model Input
Reservoir information, geotechnical parameters, saturation data, injection data, etc.
Model Output
Simulated pressure, flow rates, saturation changes
Risks Behavior
Considered
Induced seismicity,storage resource
Relevant
Permitting Phase
All
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Review and Corrective Action Plan, Testing
and Monitoring Plan, Injection Well Plugging Plan and Post-Injection Site Care and Site
Closure Plan
Last Updated
2021
Ongoing
Development
Commercial, regularupdates
Related
References
httDs://www.landmark.solutions/Nexus-Reservoir-Simulation
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A.8.10 Nonisothermal, Unsaturated-saturated Flow and Transport (NUFT)
Tool Name
Nonisothermal, Unsaturated-saturated Flow and Transport (NUFT)
Developer/Owner
Lawrence Livermore National Laboratory
Tool Type
Reservoir Simulation
Description
NUFT is a 3D multi-phase non-isothermal flow and transport model for both saturated and
unsaturated simulations. It has been extensively applied to groundwater clean up (especially
thermal alternatives), deep geologic processes, including high level nuclear waste
repositories and subsurface sequestration of CO2. In the CSS context it has been used for
reservoir-scale reactive flow modeling of CO2 injection, transport, and storage. It has also
been used to understand the impact of leaked C02on aquifers.
Tool Licensingand
Access
Lawrence Livermore National Security, LLC. Can be licensedfrom:
httDs://iDo.llnl.eov/technoloeies/software/nuft
Model Input
Porosity, permeability, clay fraction, clay correlation length, mineralogy of geological
formation, initial brine composition, reservoir pressure and C02saturation, leakage location
and flux
Model Output
C02satu ration, TDS, and pressure in shallow ground water aquifers. Can be coupled to
geophysical models to obtain geophysical monitoring data
Risks Behavior
Considered
Leakage risk and impact
Relevant
Permitting Phase
Injection and post-injection
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Re vie wand Corrective Action Plan, Testing and
Monitoring Plan, Post-injection Site Care and Site Closure Plan
How the Tool is
Used
The tool can be used to run simulations to determine pressure, the extent of the plume,
concentration of species, etc. Multiple simulations can be runby varying input parameters.
Last Updated
2019
Ongoing
Development
Yes
Ease of Use
No graphical user interface. Some level of proficiency with running codes viacommandline
is necessary
Computational
Speed
Run time is dependent on several factors. It is computation ally expensive and has to be run
in parallel on multiple cores.
Tool Verification
Yes. Some of the verification is shown in the reference below
Related
References
Hao, Y.; Sun,Y.; Nitao, J. J. Chapter9: Overview of NUFT: A versatile numerical model for
simulating flow and reactive transport in porous media; 2010. doi:10.2172/948987.
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A.8.11 PFLOTRAN
Tool Name
PFLOTRAN
Developer/Owner
Glen Hammond (PNNL)/Multi-labcollaboration
Tool Type
Reservoir Simulation
Description
PFLOTRAN is an open-source, state-of-the-art massively parallel subsurface flow and
reactive transport code. PFLOTRAN solves a system of generally nonlinear partial differential
equations describing multiphase, multicomponent, and multiscale reactive flow and
transport in porous mate rials. The code is designed to run on massively parallel computing
architectures as well as workstations and laptops. Parallelization is achieved through
domain decomposition using the PETSc (Portable Extensible Toolkit for Scientific
Computation) libraries. PFLOTRAN has been developedfrom the ground up for parallel
scalability and has been run on up to 218 processor cores with problem sizes up to 2 billion
degrees of freedom. PFLOTRAN is written in object oriented, free formatted Fortran 2003.
The choice of Fortran over C/C++was based primarily on the need to enlist and preserve
tight collaboration with experienced domain scientists, without which PFLOTRAN's
sophisticated process models would not exist. The reactive transport equationscan be
solved using either a fully implicit Newton-Raphson algorithm or the less robust operator
splitting method.
Tool Licensingand
Access
httDs://www.Dflotran.ore/index.html
Model Input
Model domain, rockproperties, boundary conditions, component properties, reaction rates
Model Output
Spatial and temporal changes in pressure, C02 saturation, and constituent concentrations.
Risks Behavior
Considered
Leakage risk, environmental risk
Relevant
Permitting Phase
Site screening, site characterization, injection, post-injection
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan, Testing and
Monitoring Plan, Post InjectionSite Care and Site Closure Plan
How the Tool is
Used
PFLOTRAN can be used as a reservoir simulation tool for a GCS project.
Last Updated
November 11,2021
Ongoing
Development
Yes
Ease of Use
The tool does not have a graphical user interface but may be executed by providing an input
file created using a simple text editor. Computer programming skills are not required but an
understanding of geology is.
Computational
Speed
PFLOTRAN simulations are designed to be run in parallel, which greatly reduces
computational speeds.
Tool Verification
httDs://www.Dflotran.ore/documentation/
Related
References
httDs://www.Dflotran.ore/index.html
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A.8.12 STOMP-CQ2
Tool Name
ST0MP-C02
Developer/Owner
PNNL
Tool Type
Reservoir Simulation
Description
The STOMP-C02simulatorsolvesthreecoupled conservation equations: water mass,
CO2 mass, and salt mass; with the potential for aqueous and gas mobile phases and a
precipitated salt solid phase. ST0MP-C02E addition ally solves the energy equation. The
ECKEChem Module, usedto simulate geochemical reactions, isavailablefor ST0MP-C02.
Tool Licensingand
Access
h ttD s: //www. d n n 1 .eo v/eet- sto m p
Model Input
Domain grid, rockzonation, porosity, permeability, saturationfunction, relative permeability
function, injection and/or legacy well characteristics, initial and boundary conditions
Model Output
Spatial and temporal distribution of dissolved, gaseous or supercritical CO2, brine salinity,
pressure, temperature, aqueous species concentrations, rock mineral volumes
Risks Behavior
Considered
Leakage risk, environmental risk
Relevant
Permitting Phase
Site screening, site characterization, injection, post-injection
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan, Testing and
Monitoring Plan, Post InjectionSite Care and Site Closure Plan
How the Tool is
Used
As an example, STO MP-C02 was used for the FutureGen2.0 UIC permit application to
develop models of C02 injection and C02 leakage at the site.
AOR: httDs://archive.eDa.eov/reeion5/water/uic/futureeen/web/Ddf/attachament-b.Ddf
PISC: httDs://archive.eDa.eov/reeion5/water/uic/futureeen/web/Ddf/attachment-e-2.Ddf
Monitoring:
Vermeul,V. R.; Amonette, J. E.; Strickland, C.E.; Williams, M. D.; Bonneville, A. An overview
of the monitoring program design forthe FutureGen 2.0 CO2 storage site.
International Journal of Greenhouse Gas Control 2016,51,193-206.
10.1016/j.ijggc.2016.05.023.
Since then, the capability to simulate leakage through legacy wells has been added.
Last Updated
Octoberl5,2021
Ongoing
Development
STOMP is still under development, has an active user community, and support forthe tool is
available at httDs://www.Dnnl.eov/Droiects/stomD
Ease of Use
The tool does not have a graphical user interface, but may be executed by providing an
in put file created using a simple text editor. Users do not need computer programmingskills
to use ST0MP-C02, butsome knowledge of hydrogeology is required.
Computational
Speed
Computational speed is inversely proportional to the number of grid cells, time steps, and
components selected by the user.
Tool Verification
Example applications comparing STO MP results to published benchmark problems are
providedwith the sourcecode.
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Related h ttps: //www.p n n I .go v/p ro iects/sto mp
References https://stomp-usereuide.pnnl.gov
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A.8.13 TOUGH3-ECQ2N/M or iTOUGH2-ECQ2N/M
Tool Name
TOUGH3-EC02N/Mor iT0UGH2-EC02N/M
Developer/Owner
Lawrence Berkeley National Laboratory
Tool Type
Reservoir Simulation
Description
The TOUGH ("Transport Of Unsaturated Groundwater and Heat") suite of software codes are
multi-dimensional numerical modelsforsimulatingthe coupledtransport of water, vapor,
non-condensablegas, and heat in porous and fractured media. Developed at the Lawrence
Berkeley National Laboratory (LBNL) in the early 1980s primarily forgeothermal reservoir
engineering, the suite of simulators is now widely used at universities, government
organizations, and private industry for applications to nuclear waste disposal, environmental
remediation problems, energy production from geothermal, oil and gas reservoirs as well as
gas hydrate deposits,geological carbon sequestration, vadose zone hydrology, and other
uses that involve coupled thermal, hydrological, geochemical, and mechanical processes in
permeable media. The TOUGH suite of simulators is continually updated, with newequation-
of-state (EOS) modules being developed, and refined process descriptions implemented into
the TOUGH framework (see the overview of the TOUGH development history). Notably, EOS
property modules for mixtures of water, NaCI, and C02 has been developed and is widely
used for the analysis of geologiccarbon sequestration processes.
Tool Licensingand
Access
The tool is licensed throueh Berkelevlab marketplace at: httDs://marketDlace.lbl.eov/
Model Input
Model domain, discretized grids, hydrological parameters of the geological formation,
operational parameters (e.g., injection rate), characteristic curves (e.g., relative permeability
and capillary pressure functions)
Model Output
Pressure, temperature and CO2 saturation (or mass fraction is it is fully liquid saturated)
within the model domain
Risks Behavior
Considered
Leakage risk
Relevant
Permitting Phase
Injection, post-injection
Class VI Permit
Element
Addressed
Site Screening, Area of Review and Corrective Action Plan, Post-Injection Site Care and Site
Closure Plan
How the Tool is
Used
Identify questions to be addressed, collect site data, build site model, calibrate the model
(match model outputto observed data), use the calibrated modelto predict
Last Updated
Officially 2017
Ongoing
Development
The tool has an active user community. Researchers update the tools occasionally for their
research need. Like any other large simulation codes, when occasion ally a bug is suspected,
the development team will work on fixingthe bug. The development team provides short
courses on a regular basis for the tool. There is also a user forum where the user community
and development team try to provide support.
Ease of Use
The tool hascommercialgraphical user interfaces. Users should havea basic understanding
of numerical models and multiphase flow to use the tool. Computer programming skills are
not required but may be helpful. The tool is written in Fortran. Basic knowledge on compiling
a computer code may be helpful unless the user has someone else to help this aspect.
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Computational
Speed
The tool can handle runsin parallel. The speed depends on the problem size and the
difficulty of the problem itself. Understandingin numerical models may help to design a
problem that has a good balance between the efficiency and accuracy of the problem
required.
Tool Verification
Related documentation and research papercan befoundat
httDs://toueh.lbl.eov/docu mentation/
Related
References
Pan, L.; Spycher, N.; Doughty, C.; Pruess, K. EC02NV2.0:A TOUGH2 Fluid Property Module
for Mixtures of Water, NaCland CO2; Report LBNL-6930E; Lawrence Berkeley
National Laboratory, Berkeley, CA, Feb 2015. A listof websites, manuals, and
publications that provide additional insight into the tool.
Pruess, K. EC02M:A TOUGH2 Fluid Property Module for Mixtures of Water, NaCI, andCC>2,
Including Super- and Sub-Critical Conditions, and Phase Change Between Liquid and
Gaseous CO2; Report LBNL-4590E; Lawrence Berkeley National Laboratory,
Berkeley, CA,2011.
Pruess, K. ECO 2 N: A TOUGH2 Fluid Property Module for Mixtures of Water, NaCI, andC02;
Report LBNL-57952; Lawrence Berkeley National Laboratory, Berkeley, CA, 2005.
(superseded by Pan etal., 2015).
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A.8.14 TOUGH-FLAC
Tool Name
TOUGH-FLAC
Developer/Owner
Jonny Rutqvistat LBNLand co-workers have developed the linking of TOUGH2 and FLAC3D
Tool Type
Reservoir Simulation
Description
TOUGH-FLAC is based on the linking of TO UGH-family multiphase flu id flow and heat
transport simulators with the FLAC3Dgeomechanics simulator.
Tool Licensingand
Access
The user would needaTOUGH2 orTOUGH3 license from LBNL(httDs://toueh.lbl.eov/) and
a FLAC3D license from Itasca ConsultingGroup
(httD://www.itascace.com/software/FLAC3D). There iscurrentlv no formal license
developed for the coupling routines between T0UGH2 and FLAC3D, has only been
provided under research collaborations.
Model Input
Model geometry, properties forfluid flow (e.g., porosity, permeability), thermal (e.g.,
thermal conductivity) and geomechanics (e.g., Elastic modulus), initial conditions (pressure,
temperature, stress), boundary conditions (e.g., fixed pressure, temperature,
displacement, stress, flow)
Model Output
Distribution and evolution of fluid flow, pressure, thermal flow, temperature, stress, strain,
and displacements
Risks Behavior
Considered
Leakage risks through caprockand alongfaults, inducedseismicity, well integrity
Relevant
Permitting Phase
Site characterization, injection, post-injection
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan, Testing
and Monitoring Plan, Post Injection Site Care and Site Closure Plan, Stimulation Program
How the Tool is
Used
After initial site screening,thetool can be used forevaluatinggeomechanical performance
of an injection site, to identify areas of concern, e.g., faults, caprock, basement for the
potential of induced seismicity or leakage, in eluding fault activation.
Last Updated
It is continuously updated and applied to a wide-range of problems related to subsurface
coupled processes.
Ongoing
Development
Yes
Ease of Use
The FLAC3D codes has a graphical interface that can be used for pre- and post-processing.
T0UGH2 output such as pressure, saturation, and temperature that can be displayed in the
FLAC3Dgraphical interface.The userneedsageosciences background, with experiencein
coupled thermal-hydraulic-mechanical modeling. The user does not need advanced
programmingskills.
Computational
Speed
Latestversions included T0UGH3and FLAC3DV7, includes parallel processing and can run
few million grid blocks if desired.
Tool Verification
Each of the componentsTOUGH2and FLAC3D have been extensively verified and validated
as documented in user's manuals and otherdocuments.The TOUGH-FLAC couplings has
been verified and published in an extensive numberof peer-reviewed publications.
Related
References
For FLAC3D: httD://www.itascace.com/software/FLAC3D
For TOUGH: httDs://toueh.lbl.eov/
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General for TOUGH-FLACand linking:
Cappa, F.; Rutqvist, J. Impact of CC>2geological sequestration on the nucleation of
earthquakes. Geophysical Research Letters 2011,38, L17313.
Cappa, F.; Rutqvist, J. Modelingof coupled deformation and permeability evolution during
fault reactivation induced by deep underground injection of C02. International
Journal of Greenhouse Gas Control 2011,5,336-346.
Cappa, F.; Rutqvist, J. Seismic rupture and ground accelerations induced by CO2 injection in
the shallow crust. Geophysical Journal International 2012,190,1784-1789.
Cappa F.; Rutqvist, J.; Yamamoto, K. Modeling crustal deformation and rupture processes
related to upwellingof deep CO 2 rich flu ids during the 1965-1967 Matsushiro
Earthquake Swarm in Japan .Journal of Geophysical Research 2009,114, B10304.
Figueiredo, B.; Tsang, C. F.; Rutqvist, J.; Bensabat, J.; Niemj A. Coupled hydro-mechanical
processes and fault reactivation induced by CO 2 Injection in a three-layer storage
formation. International Journal ofGreenh ouse Gas Control 2015,39,432-448.
Jeanne, P.; Guglielmi, Y.; Cappa, F.; Rinaldi, A. P.; Rutqvist, J. The effects of lateral property
variations on fault-zone reactivation by fluid pressurization: application to CO2
pressurization effects within major and undetected fauIt zones. Journat of
Structural Geology 2014,62,97-108.
Kim, H.-M.; Rutqvist, J.; Bae, W.-S. Sensitivity analysis for fault reactivation in potential
C02-EORsite with multi-layers of permeable and impermeableformations.
Geosystem Engineering 2014,17,253-263.
Konstantinovskaya, E.; Rutqvist, J.; Malo, M.CO2 storage and potential fault instability in
the St. Lawrence Lowlands sedimentarybasin (Quebec, Canada): Insights from
coupled reservoir-geomechanical modeling. International Journal of Greenhouse
Gas Control 2014,22,88-110.
Lee, J.; Min, K.-B.; Rutqvist, J. Probabilistic analysis of fracture reactivation associated with
deep underground C02 injection. Rock Mechanics and Rock Engineering 2013,46,
801-820.
Mazzoldi, A.; Rinaldi, A. P.; Borgia, A.; Rutqvist, J. Induced seismicitywithin geologiccarbon
sequestration projects: Maximum earthquake magnitude and leakage potential.
International Journal of Greenhouse Gas Control 2012,10,434-442.
Pruess, K.; Garcia,J.; Kovscek, J.T.; Oldenburg,C.; Rutqvist, J.; Steefel, C.;Xu,T. Code
Intercomparison Builds Confidence in Numerical Simulation ModelsforGeologic
Disposal of CO2. Energy 2004,29,1431-1444.
Rinaldi, A. P.; Rutqvist, J. Modelingof deep fracture zone opening and transient ground
surface uplift at KB-502 CO2 injection well, In Salah, Algeria. InternationalJournal
of Greenhouse Gas Control 2013,12,155-167.
Rinaldi, A. P.; Jeanne, P.; Rutqvist, J.; Cappa, F.; Guglielmi, Y. Effects of fault-zone
architecture on earthquake magnitude and gas leakage related to CO 2 injection in
a multilayered sedimentary system. Greenhouse Gases: Science and Technology
2014,4,99-120.
Rinaldi, A. P.; Rutqvist, J.; Cappa F.Geomechanical effects on CO 2 leakage through fau It
zones during large-scale underground injection. InternationalJournalof
Greenhouse Gas Control 2014,20,117-131.
Rinaldi, A. P.; Vilarrasa, V.; Rutqvist, J.; Cappa F. Fault reactivation during C02
sequestration: Effectsofwell orientationon seismicity and leakage. Greenhouse
Gas Sciences and Technology 2015,5,1-12.
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Rutqvist, J.; Tsang, C.-F. A study of caprockhydromechanical changes associated with CO 2
injection into a brine aquifer. Environ mental Geology 2002,42,296-305.
Rutqvist J. Status of the TO UGH-FLAC simulator and recent applications related to coupled
fluid flow and crustal deformations. Computers & Geosciences 2011,37,739-750.
Rutqvist, J. The geomechanicsof CO2 storage in deep sedimentary formations.
International Journal ofGeotechnicaland Geological Engineering 2012,30,525-
551.
Rutqvist, J.; Birkholzer, J.; Cappa, F.; Tsang, C.-F. Estimating maximum sustainable injection
pressure during geological sequestration of CO 2 using coupled fluid flow and
geomechanical fault-slip analysis. Energy Conversion and Management 2001,48,
1798-1807.
Rutqvist,J.; Birkholzer,J.T.; Tsang,C. F.Coupled Reservoir-Geomechanical Analysis of the
Potential for Tensile and Shear Failure Associated with C02 Injection in
Multilayered Reservoir-Caprock Systems. Int. J. Rock Mech. & Min. Sci 2008,45,
132-143.
Rutqvist, J.; Cappa, F.; Rinaldi, A. P.; Godano, M. Modeling of induced seismicity and
ground vibrations associated with geologic C02 storage, and assessing their effects
on surface structuresand human perception. International Journal of Greenhouse
Gas Control 2014,24,64-77.
Rutqvist, J.; Vasco, D.; Myer, L. Coupled reservoir-geomechanical analysis of CO2 injection
and ground deformations at In Salah, Algeria. Int. J. Greenhouse Gas Control 2010,
4,225-230.
Rutqvist, J.; Wu, Y.-S.; Tsang, C.-F.; Bodvarsson, G. A Modeling Approach for Analysis of
Coupled Multiphase Fluid Flow, HeatTransfer, and Deformation in Fractured
Porous Rock. Int. J. Rock Mech. & Min. Sci. 2002,39,429-442.
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A.8.15 TOUGHREACT
Tool Name
TOUGHREACT
Developer/Owner
Lawrence Berkeley National Laboratory
Tool Type
Reservoir Simulation
Description
TOUGHREACTis a numerical simulation program forchemically reactive non-isothermal
flows of multiphase fluids in porous and fractured media, developed by introducing
reactive chemistry into the multiphase flow code TOUGH2.
Tool Licensingand
Access
The tool is licensed throueh LBNL at website: httDs://toueh.lbl.eov/software/toueh react/
and distributed via Berkeley Lab Marketplace.
Model Input
Model inputs include hydrological information of the aquifer/reservoirsuch as porosity,
permeability, and geochemical information of the system such as groundwater
composition and mineralogical composition.
Model Output
The model generates the spatial and temporal distribution of pressure, temperature,
saturation, and concentrations of chemical components.
Risks Behavior
Considered
The model simulatesthe leakage riskand otherenviron mental risk suchas the change of
groundwaterin response to the leakage of C02.
Relevant
Permitting Phase
For Class VI permit the tool can be usedfor all the phases rangingfrom site screening, site
characterization, injection to post-injection, especially if geochemical changes are of
concern.
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan, Testing
and Monitoring Plan, Post InjectionSite Care and Site Closure Plan
How the Tool is
Used
The tool can be used to quantify hydrological and geochemical changes atany phases of
the permitin conjunction with site characterization and monitoring.
Last Updated
A major update ofthe codewasdone in 2014.
Ongoing
Development
The tool has been widely used bothdomesticallyand international formany underground
engineering applications and has been supported by the scientist from LBNL.
Ease of Use
The tool does not have a graphical user interface, but a graphical interface had been
developed by third party. Users does not need computer programming skills to use the
tool, but knowledge on the underground hydrology and geochemistry is needed.
Computational
Speed
The model has been upgraded for computational efficiency and one of the most efficient
codes for simulating multiphase flow and reactive transport. Computation time is usually
not a problem, but the simulation can be time consuming if the problem is very big and
complicated.
Tool Verification
The tool been verified by analytical solution and testingproblems, which is documented in
the manual ofthe code.
Related
References
The manual can be found on the website: httDs://toueh.lbl.eov/software/touehreact/
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A.8.16 Two-Phase Flow Model (TPFLOW)
Tool Name
TPFLOW (Two-Phase Flow Model)
Developer/Owner
Abdullah Cihan/LBNL
Tool Type
Reservoir Simulation
Description
TPFLOW computes pressure and saturation changes in subsurface by solvingthe coupled
nonlinear partial differential equations for pressure and saturation using the Finite Volume
method.
Tool Licensingand
Access
The code is accessible through the developerand LBNL
Abdullah Cihan: httDs://eesa.lbl.eov/Drofiles/abdullah-cihan/
Model Input
Model geometry, numerical grid (ID, 2D, and 3D Cartesian, or 2D axisymmetriccylindrical
coordinates), hydrogeological and two-phase flow properties (relative permeability and
capillary pressure functions) in the domain, and initial and boundary conditions, provided
through asingle inputfile
Model Output
Time-de pendent pressure and saturation as both contour data and observation point data
(user-selected). Users can also obtain leakage fluxes at any arbitrary selected points.
Risks Behavior
Considered
CO2 leakage risk
Relevant
Permitting Phase
Site screening, injection, and post-injection
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Re vie wand Corrective Action Plan, Testing
and Monitoring Plan, Post-lnjectionSite Careand Site Closure Plan, Emergency and
Remedial Response Plan
How the Tool is
Used
The tool can be used to estimate evolution of pressure and saturation in subsurface.
Last Updated
The tool was last updated in March 2021.
Ongoing
Development
The development was mainly completed, but a user manual needs to be developed. There
is no active user community. The code hasbeenused by graduate students and postdocs.
Ease of Use
No user interface. The code uses one in put text file and generates output files that can be
directly dragged intoTecplot software for plotting the results. The users do not need
programing skills, butsome basic knowledge abouttwo-phaseflowin subsurfaceand
modeling is needed.
Computational
Speed
The code is partially parallelized and it may be used to simulate CO2 migration efficiently.
Because the phase changes of C02(sc-liq-gas-ice) and chemical reactions are not included,
the code may be computationally more efficient compared to other multiphase simulators
taking into accountthose processes. The code also has a versionthat can be run as a
vertically-integrated model (semi-3Dmodel), whichmightbe usedfor modeling a single-
layer reservoir with varying thickness.
Tool Verification
Verified with analytical solutions, other numerical models and laboratory data. Some of
these verifications were documented in the published literature.
Related
References
There is currently no published user manual for the code.
The following references includeeither descriptions or applications of the code:
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Cihan, A.; Birkholzer, J.T.; lllangasekare, T. H.; Zhou, Q. A modeling approach to represent
hysteresis in capillarypressure-saturation relationship based on flu id connectivity
in void space. Water Resources Research 2014,50. doi:10.1002/2013WR014280.
Cihan, A.; Birkholzer, J. T.; Trevisan, L.; Gonzalez-Nicolas, A.; lllangasekare, T. H.
Investigation of representing hysteresis in macroscopic models of two-phase flow
in porous media using intermediate scale experimental data. Water Resources
Research 2017,53,199-221. doi: 10.1002/2016WR019449.
Cihan, A.; Birkholzer, J. T.; Bianchi, M. Optimal Well Placement and Brine Extraction for
Pressure Management du ring CO2 Sequestration, International Journal of
Greenhouse Gas Control 2015,42,175-187.
Cihan, A.; Bhuvankar, P.; Birkholzer, J.T. Risk of wellbore leakage to shallow aquifers in
geologic carbon sequestration: Numerical studies on the effects of CO 2 property
changesin multilayeredsystems; underpreparation, 2021.
Cihan, A.; Wang, S.; Tokunaga, T. K.; Birkholzer, J.T. The role of capillary hysteresis and
pore-scale heterogeneity in limiting the migration of buoyant immiscible fluids in
porous media. Water Resources Research 2018,54,4309-4318.
Gonzalez-Nicolas, A.; Trevisan, L.; lllangasekare,T. H.; Cihan, A.; Birkholzer, J.T. Enhancing
Capillary Trapping Effectiveness thro ugh Proper Time Scheduling of Injection of
Supercritical CC>2in Heterogeneous Formations. Greenhouse Gases: Science and
Technology 2017, 7,339-352.
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A.9 RESOURCE ESTIMATION
Estimating the C02 storage capacity of a reservoir is necessary to characterize its potential for
GCS. Tools in this category accept general information about a potential storage interval and
return an estimate of the quantity of CO2 that can be stored in the formation.
A.9.1 Storage Prospective Resource Estimation Excel Analysis (CO2 SCREEN)
Tool Name
CO2-SCREEN (Storage prospective Resource Estimation Excel aNalysis)
Developer/Owner
National Energy Technology Laboratory: Angela Goodman, Sean Sanguinito, Foad Haeri,
Grant Bromhal
Tool Type
Resource Estimation
Description
CO2-SCREEN (Storage prospective Resource Estimation Excel aNalysis) is a tool
developed by the U.S. DOE's NETL to provide prospective carbon storage resource
estimates in subsurface formations to establish the scale of carbon capture and storage
activities for governmental policy and commercial project decision-making. CO2-SCREEN
is coded in Python with a Java based graphical user interface which provides robust
probabilistic estimates within an easy-to-use framework. C02-SCREEN is capable of
ge nerating prospective carbon storage estimates for various geologic formations
including saline, shale, and residual oil zones.
Tool Licensingand
Access
Open-source: Can be downloaded from: httDs://edx.netl.doe.eov/dataset/co2-screen
Model Input
The CO2-SCREEN tool accepts user in puts for physical parameters and storage efficiency
factor terms, which differas a function of formationtype. Physical parameters are
geologic reservoir properties (e.g., area, thickness, porosity, etc.) that are used to
calculate the total volume of a formation or region of in te rest while storage efficiency
factors (e.g., net-to-total thickness, effective-to-total porosity, etc.) reducethe total
volume to only the volume available and accessible to CO 2 storage.
The physical parameter data are dependent on formationtype based on howCChis
stored. CO2 is stored as a free phase for all formation types (saline, shale, residual oil
zones) and required physical parameters in elude total area, gross thickness, total
porosity, and temperature, and pressure of the CO 2 injection depth. Because of the
higherclayand organiccontentin shales, C02can be storedasasorbed phase.To
account for this, additional physical parameters include total organic con tent, Langmuir
slope, and Langmuir y-intercept. In residual oil zones, a significant portion of C02can be
stored as a dissolved phase in the residual oil and additional physical parameters
include irreducible water saturation, residual oil saturation, and concentration of CO 2 in
oil. All physical parameter in puts require mean values, and a standard deviation can be
provided to account for uncertainties. The tool automatically calculates density of CO 2
based on pressure and temperature inputs.
Efficiencyfactor ranges are also dependent on formationtype. Forthe most accurate
CO2 storage estimations, it is recommended that region-specific data are used for
efficiencyfactor ranges. Since these data are not always readily available, CO 2-SCREEN
has the unique capability to provide users efficiencyfactor ranges based on reservoir
modeling and numerical simulations. For saline and residual oil zone formations,
efficiency factors have beensimulated for a variety of de positional environments (IEA,
2009). Userscan select the depositional environment most relevantto their datasetto
auto-populate a set of efficiency factor ranges. For shale formations, well-scale
efficiency factors (effective-to-total-porosity and effective-to-total-sorption) were
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simulated as afunction of injection time and users can selectan injection time to auto-
populate these values. These ranges can be further modified or entered manually to
accountfor specific datasets.
Model Output
CO2-SCREEN is a software tool that is coded in Python with a Java based graphical user
interface. CO2-SCREEN applies user entered data into embedded CO2 storage equations
(developed by the U.S. DOE) and uses Monte Carlosimulation to calculate probability
estimates for prospective CO2 storage capacity.
Another key feature of CO 2-SCREEN is its ability to estimate CO 2 storage resources for a
gridded formation. Data from multiple we lis can be entered for the physical parameters
into separate spatially divided grid cells to accountfor geologic heterogeneity within a
single formation. By incorporating specific ranges for storage efficiencyfactorterms on
a "grid cell by grid cell" basis, the tool can provide more localized storage estimates and
minimize uncertainties associated with formation heterogeneity.
Relevant Permitting
Phase
Site Screening, Site Characterization
Class VI Permit
Element Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan
How the Tool is
Used
The C02-SCREENtool provides a user-friendly platform for estimating the prospective
C02 storage potential of geologic formation sat the national-, regional-, basin-and
formation-scale. The tool can be applied at the initial screening stagesof a projectusing
only limited publicly available geophysical data to provide a preliminary estimate. The
tool can be used to refine the estimate and reduce its uncertainty as the project
progresses to the commercial scale as site-specific geophysical data become more
readily available. It also provides a consistent method to calculate CO2 storage potential
while allowing for direct comparison of prospective CO2 storage estimates between a
variety of organizations including government agencies and independent research
studies.
Last Updated
June 28,2021
Ongoing
Development
Yes
Ease of Use
CO2-SCREEN is a software tool that is coded in Python with a Java based graphical user
interface. It is intended to be easy to use and is free to use.
Computational
Speed
Simulations take between 30and 60 secondsto complete.
Tool Verification
No
Related References
Azenkeng, A.; Mibeck, B. A. F.; Kurz, B. A.; Gorecki, C. D.; Myshakin, E. M.; Goodman, A.
L.; Azzolina, N.A.; Eylands, K. E.; Butler,S. K. An Image-based Equation for
Estimatingthe C02Storage Resource Capacity of Organic-rich Shale
Formations. InternationalJournalof Greenhouse Gas Control 2020,98,103038
Goodman, A.; Sanguinito,S.; Levine, J. Prospective CO2Saline Resource Estimation
Methodology: Refinementof Existing DOE-NETLMethods Based on Data
Availability. International Journal of Greenhouse Gas Control 2016,54,242-
249.
Goodman, A.; Hakala, A.; Bromhal, G.; Deel, D.; Rodosta,T.; Frailey,S.; Small, M.; Allen,
D.; Romanov,V.; Fazio,J.; Huerta, N.; Mclntyre, D.; Kutchko, B.; Guthrie,G. U.S.
DOE methodology for the development of geologic storage potential for
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carbon dioxideatthe national and regional scale. Int.J. of Greenhouse Gas
Control 2011,5,952-965.
Goodman, A.; Bromhal, G.; Strazisar, B.; Rodosta,T.; Guthrie, W.; Allen, D.; Guthrie,G.
Comparison of methods for geologic storage of carbon dioxide in saline
formations. International Journal of Green house Gas Control 2013,18,329-
342.
Levine, J.S.; Fukai, I.; Soeder, D.J.; Bromhal, G.; Dilmore, R. M.; Guthrie, G. D.; Rodosta,
T.; Sanguinito,S.; Frailey,S.; Gorecki, D.; Peck, W.; Goodman, A. L. U.S. DOE
NETL Methodology for Estimating the Prospective CO2 Storage Resource of
Shales at the National and Regional Scale. Int. J. of Greenhouse Gas Control
2016,51,81-94.
Myshakin, E.; Singh, H.; Sanguinito, S.; Bromhal, G.; Goodman, A.Simulated Efficiency
Factors for Estimating the Prospective CO 2 Storage Resource of Shales.
International Journal of Greenhouse Gas Control 2018, 76,24-31.
Myshakin, E.; Singh, H.; Sanguinito, S.; Bromhal, G.; Goodman, A. Flow Regimes and
Storage Efficiencyof CO2 Injected into Depleted Shale Reservoir. Fue/2019,
246,169-177.
Sanguinito, S.; Goodman, A.; Sams, J. CO2-SCREENT00I: Application to the Oriskany
Sandstone to Estimate Prospective C02Storage Resource. International
Journal of GreenhouseGas Control 2018, 75,180-188.
Sanguinito,S.; Singh, H.; Myshakin, E.; Goodman A.; Dilmore, R.; Grant,T.; Morgan, D.;
Bromhal, G.; Warwick, P. D.; Brennan,S.T.; Freeman, P. A.; Karacan, C. O.;
Gorecki, C.; Peck,W.; Burton-Kelly, M.; Dotzenrod, N.; Frailey, S.; Pawar, R.
U.S. DOE NETL methodology forestimatingthe prospective CO 2 storage
resource of residual oil zones at the national scale. International Journal of
Greenhouse Gas Control 2020,96,103006.
Sanguinito,S.; Goodman, A.; Haeri, F. CO2 Storage prospective Resource Estimation
Excel aNalysis (CO2-SCREEN) User's Manual; DO E/NETL-2020/2133; NETL
Technical Re port Series; U.S. Departmentof Energy, National Energy
Technology Laboratory: Pittsburgh, PA, 2020; p 36. DOI: 10.2172/1617640.
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A.9.2 Offshore CO2 Saline Storage Calculator
Tool Name
Offshore CO2 Saline Storage Calculator
Developer/Owner
National Energy Technology Laboratory; Developers: Lucy Romeo, Patrick Wingo, Aaron
Barkhurst, Burt Thomas, KellyRose
Tool Type
Resource Estimation
Description
The Offsh ore CO2 Saline Storage Calculator applies the logic of the Offshore CO 2 Saline
Storage (OCSS) Methodology to calculate long-term storage resource (in gigatons)
distributions for offshore saline environments. The OCSS Methodology (Cameron et al.,
2018) was developed by tailoring the U.S. DOE methodology (Good man etal., 2016) for
offshore environments. The OCSS Methodology accounts for how CO 2 de nsity changes
with the overlying water column, and how the unlithified, more porous and permeable
sediment be haves differently in marine saline geologic formations. Built in Python 3.7,
this stand-alone tool uses all possible combinations of in put variables (i.e., reservoir
area, height, porosity, efficiency) to calculate storage potential. Furthermore, the tool
enablesthe application of spatial data todefine key variables, such as area, while also
accounting for setback distances from potential leakage pathways.
Tool Licensingand
Access
Desktop version of the tool is available for download on Energy Data exchange.
Citation:
Romeo, L.; Wingo, P.; Barkhurst, A.; Thomas, R.; Rose, K. Offshore CO2 Saline Storage
Calculator. 2020. httDs://edx.netl.doe.eov/dataset/offshore-co2-saline-storaee-
calculator DO 1:10.18141/1607787
Model Input
Data representing reservoir area, height, porosity, lithologyand depositional
environment, microscopicand volumetric displacement, and efficiencyare needed to
run the Calculator. A dataset of interpreted petrophysicalwell logs was developed and
this data was applied (Bean etal., 2020) with Su bsurface Trend Analysis™ STA domains
representing areas of similar geologic histories (Mark-Moseretal., 2020; Rose etal.,
2020) to evaluate geologic storage potential in the Northern Gulf of Mexico. These data
are available for furtherapplication.
Bean, A.; Romeo, L.; Justman, D.; DiGiuNo, J.; Miller, R.; Cameron, E.; Rose, K.
Petrophysical Well Log Interpretation Dataset, Mar 5,2020.
httDs://edx.netl.doe.eov/dataset/DetroDhvsical-well-loe-interDretation-dataset.
DOI: 10.18141/1560053
Mark-Moser, M.; Miller, R.; Rose, K.; Bauer, J. Subsurface Trend Analysis Domains for the
Northern Gulf of Mexico: 2020. httDs://edx.netl.doe.eov/dataset/subsurface-
trend-analvsis-domains-for-the-northern-eulf-of-mexico doi:10.18141/1606228
Rose, K. K.; Bauer, J. R.; Mark-Moser, M. A systematic, science-driven approach for
predicting subsurface properties. Interpretation 2020,8, T167-T181.
Input Parameters
• Data Table - Data table (CSVor TXTfile) containing numericfields associated with
inputs.
• Net Height - Field from Data Table re presenting the height (meters, kilometers, feet,
or miles) of the sands available for storage beneath a shale sea.
• Total Height - Field from Data Table representing the total height (meters,
kilometers, feet, or miles) of the reservoir.
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• Lithology and Depositional Environment(s) - A rangeof porosity efficiency (portion
of pore space in the sands available for storage) based on selected lithology and
depositional environment(s) (Gorecki etal., 2009).
• Total Porosity - Fie Id from Data Table representing the total fraction of porosity in
the sands.
• Volumetric Displacement- Fieldfrom DataTable representingthe fraction of pore
space adjacent to the injection point that is contacted by CO2 (Gorecki etal., 2009);
can be based on lithologyand depositional environment(s).
• Microscopic Displacement- Field from DataTable representingthe fraction of
brine-filled pore volume that can be replaced by C02 (Gorecki etal., 2009); can be
based on lithology and depositional environment(s).
• C02 Density
o Density- Field from DataTable representingCO2densities (kilogramspercubic
meter) atreservoirmid-depths.
or
o Temperature atSeafloor-Constant temperature (Celsius or Fahrenheit) atthe
seafloor of the Total Area of the saline formations.
o Temperature Gradient-Subseafloortemperature (Celsius or Fahrenheit)
gradient per depth (meters, kilometers, feet, or miles).
o Top Reservoir Depth - Field in DataTable representingtop reservoirdepth(s)
(meters, kilometers, feet, or miles) atthe base of the sealing shale.
o Bottom Reservoir Depth - Field in DataTable representing bottom reservoir
depth(s) (meters, kilometers, feet, or miles).
o Water Depth
¦ Water Depth Field - Field in DataTable representingwater depth(s)
(meters, kilometers,feet, or miles).
or
¦ Bathymetry Raster - Continuous rater representingwater depth (meters,
kilometers,feet, or miles).
¦ Latitude - Field in DataTable representing Ycoordinate (decimal degrees in
geographiccoordinate system) of well log location.
¦ Longitude - Field in DataTable representingX coordinate (decimaldegrees
in geographiccoordinate system) of well log location.
or
¦ Constant Water Depth-Water depth (meters, kilometers, feet, or miles) to
be associated with all reservoir logs.
• Area
o Net Area Field - Field in Data Table representing area(s) (meters-, kilometers-,
feet-, or miles-squared) of the offshore saline formations available for storage.
o Total Area Field- Field in DataTable representing total area (meters-,
kilometers-, feet-, or miles-squared) ofthe offshore saline formation,
or
o Spatial Extent- Polygon shapefile representingtotal area of the offshore saline
formation.
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o Leakage Pathway(s)-Subsurface features (point, line, or polygon shapefile(s))
or proxies at the seafloor where if injected CO2 could migrate upward from the
subsurface and into the watercolumn (faults, chemosyntheticcommunities).
0 Minimum Buffer Size - Minimum setback distance (meters, kilometers, feet, or
miles), will be used to buffer leakage pathway data.
0 Maximum Buffer Size - Maximum setback distance (meters, kilometers, feet, or
miles), will be used to buffer leakage pathway data.
0 Step Buffer Size - Step sizes (meters, kilometers, feet, or miles) from Minimum
Buffer Size to Maximum BufferSize.
Output Parameters
• Output Directory- Existing folder to where all outputs will be stored.
• Filename - Output file (CSV or TXT) containing variables for all computation
combinations. An additional file with "SummaryReport" preceding the Filename, will
be exported, which contains countand percentilevaluesforboth overall efficiency
and storage potential (gigatons).
• Distribution GraphOutputs- (Optional) Distribution histograms (PNG) and data
used to build histograms (CSV) can be output for any or all variables. Variables to
export distribution graphs from include storage resource distribution, area
efficiency, porosity efficiency, microscopic displacement, total height, CO2 density,
efficiency, height efficiency, volumetric displacement, total area, and total porosity.
• Spatial Outputs- (Optional) Shapefiles re presenting netarea(s) and buffered
leakage pathways can be exported if spatial data was provided to run the tool.
Model Output
The tool automatically outputs two files. The first is a table where each record
represents a different combination to compute gigatons of storableC02and each field
represents a variable (Area Efficiency, Height Efficiency, Porosity Efficiency, Volumetric
Displacement, Microscopic Displacement, Saline Efficiency, Total Area (m2), Total
Height(m), Total Porosity (kg/m3), CO2 density, and gigatons of storable CO2. The second
automatic output is a su mmary report contain ing count and pe rcentiles (10th, 50th- 90th)
for overall efficiency and C02 storage potential. The tool also has a series of optional
outputs, including distribution graphs, and spatial data outputs, if applicable. For each
distribution graph output, an associated CSV data table with the associated values are
also output. In addition, if users select to Calculate C02 density values, a distribution
histogram by C02phaseand associate table will also be automatically output. If spatial
data has been used to calculate Net and Total Area, the spatial output options will be
made available. These outputs are spatial data layers (shapefiles) representing Net Area
or the Buffered Leakage Pathways.
Risks Behavior
Considered
Leakage risk
Relevant
Permitting Phase
Site Screening, Area of Review and Corrective Action Plan
Class VI Permit
Element
Addressed
Area of Review
How the Tool is
Used
The Offshore CO2 Saline Storage Calculator can be applied to calculate potential long-
term storage distributionsfor an area of interest. This tool can take information from
interpreted petrophysical well logs, reservoir data, leakage pathway data, and regulatory
setback distance to quantify resource storage potential for safe saline CO2 storage.
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Last Updated
Desktop Version- February 2021
Online Version - October2021
Ongoing
Development
Yes, this tool is being developed as an on line version for integration into GeoCubeand
the NETL Common Operating Platform.
Ease of Use
The desktop and online versions of the tools have a similar graphical user interface with
help information readily accessible. Users do not need any computer programming skills
to run the tool, but should have a comprehensive understanding of their in put data and
the area where they are hoping to calculate storage efficiency for. Moreover, though this
Calculator was built specifically for offshore saline environments, it was written in
Python using stand-alone libraries, and could be adapted for other regions and scales of
interest.
Computational
Speed
Asa data-driven tool, the more inputdata results in longerruntimes.The logic ofthe
tool runs all possible variable combinationsfor efficiency, then again to calculate total
storage values. Furthermore, the runtime for the desktop tool is dependent on local
computational capabilities. Running the tool for around 50to 100 data records at a time
is recommended.The tool is capable of handlingmore,though the runtime will increase
exponentially substantially.
Tool Verification
Outcomes of this data-driven tool can currently be verified usingdata comparison,
comparison to similar studies, and peer-review. Further validation can be assessed
following the practice of long-term geologic saline storage of CO2, which is not yet
available for the northern Gulf of Mexico.
Related
References
Method and Calculator Papers:
Cameron, E.; Thomas, R.; Bauer,J.; Bean, A.; DiGiulio, J.; Disenhof,C.; Galer,S.; Jones, K.;
Mark-Moser, M.; Miller, R.; Romeo, L.; Rose, K. Estimating CarbonStorage
Resources in Offshore Geologic Environments; NETL-TRS-14-2018; NETL
Technical Report Series; U.S. Department of Energy, National Energy Technology
Laboratory:Albany, OR, 2018; p 32. DOI: 10.18141/1464460.
httDs://edx.netl.doe.eov/dataset/estimatine-carbon-storaee-resources-in-
offshore-eeoloeic-environments
Goodman, A.; Sanguinito, S.; Levine,J.S. Prospective CO2 saline resource estimation
methodology: Refinementof existing US-DOE-NETLmethods based on data
availability. InternationalJournal of Greenhouse Gas Control 2016,54,242-249.
Gorecki,C. D.; Sorensen,J. A.; Bremer, J. M.; Knudsen, D.; Smith,S. A.; Steadman, E. N.;
Harju,J. A. Development of storage coefficients for determiningthe effective
C02 storage resource in deep saline formations. In SPE International Conference
on C02Capture, Storage, and Utilization; OnePetro, 2009.
Romeo, L.; Thomas, R.; Mark-Moser, M.; Bean, A.; Bauer, J.; Rose, K. Data-driven spatially
informed offshore carbon storage efficiency and storage resource methodology.
International Journal of Greenhouse Gas Control, in preparation.
This tool is featured in:
Bauer, J.; Justman, D.; Mark-Moser, M.; Romeo, L.;Creason,C.G.; Rose, K. Exploring
beneath the basemap. Wright, D. J., Harder, C., Ed.; In GIS for Science: Applying
Mapping and Spatial Analytics, Vol 2; Esri Press: Redlands, CA,2020; pp. 51-67.
httDs://www.eisforscience.com/chaDter5/
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A. 10 RISK ASSESSMENT
Risk assessment is a necessary element of the Class VI permitting process. Tools in this category
are used to identify and/or quantify the risks associated with geologic carbon storage.
A.10.1 FEMA HAZUS
Tool Name
FEMA Hazus
Developer/Owner
FEMA open-source
Tool Type
Risk Assessment
Description
FEMA HAZUS provides standardized tools and data for estimating riskfrom earthquakes,
floods, tsunamis, and hurricanes. Hazus models combine expertise from many disciplines
to create actionable riskinformation that increases community resilience. Hazus
software is distribute das a GIS-based desktop application with a growing collection of
simplified open-source tools. Risk assessment resources from the Hazus program are
always freely available and transparently developed.
Tool Licensingand
Access
Open-source: httDs://www.fema.eov/flood-maDs/Droducts-tools/hazus
Model Input
GIS data, land use, maps, surface feature maps
Model Output
Risk analysis
Risks Behavior
Considered
Leakage, storage resource, faults, fractures, boundaries
Relevant
Permitting Phase
Site screening, site characterization
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan,
Financial Assurance Demonstration, Testing and Monitoring Plan, Injection Well Plugging
Plan, Post-lnjectionSite Care and Site Closure Plan
Last Updated
2021
Ongoing
Development
Maintained by FEMA
Related
References
httDs://www.fema.eov/flood-maDs/Droducts-tools/hazus
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A.10.2 National Risk Assessment Partnership Open-Source Integrated Assessment Model
(NRAP-Open-IAM)
Tool Name
The NRAP Open-Source Integrated Assessment Model (NRAP-Open-IAM)
Developer/Owner
National Risk Assessment Partnership, Phase II
Tool Type
Risk Assessment
Description
NRAP-Open-IAM is an open-source Integrated Assessment Model (1AM) developed by the
National Risk Assessment Partnership (NRAP) to perform risk assessment for geologic CO 2
storage (GCS). The goal of NRAP-Open-IAM is to extend beyond risk assessment into risk
management, containment assurance,and decision support. NRAP-Open-IAMbuildson
manyyears of NRAP tool developmentfor riskassessment, including the NRAP-IAM-CS
also developed by the NRAP project. The NRAP-Open-IAM builds on the functionality of
NRAP-IAM-CS with in an open-source Python framework allowing NRAP-Open-IAM to: 1)
take advantage of standard Python libraries and otheropen-source analytical libraries
written in Python; 2) be applied on multiple platforms; 3) have more flexible options of
selecting modules for a specific study; and 4) give advanced users the option to modify
the 1AM to fit their need as well as enhancing the potential forcommunity contributions
to the software.The implementation ofthe reduced-order models and analytical tools
within the NRAP-Open-IAM makes the risk assessment process computationallyefficient
enough to simulate an ope rational CO 2 storage site, potential events and various
scenarios in a probabilistic/ensemble manner. The NRAP-Open-IAM is equipped with
capabilities to: 1) inform monitoring design; 2(assess model concordance to measured
field data; 3) evaluate mitigation alternatives; and 4) provide probabilistic risk assessment
and update the risk asnewdata becomes available.
Tool Licensingand
Access
Open-Source. Can be downloaded from:
httDs://edx.netl.doe.eov/nraD/nraD-ODen-iam/
httDs://eitlab.com/NRAP/OpenlAM
Model Input
NRAP-Open-IAM models are created by linking reduced-order representations of
sophisticated component models together into a complete GCS system. Each component
model describes the structure or flow behavior in a critical element of a GCS site.
Component models are modular and are designed to be interchangeable. Users build
NRAP-Open-IAM models by selecting component models and specifying in puts that
represent the characteristicsof their GCS site. Inputs to NRAP-Open-IAM component
models can either be specified as a single value or a range of values. If a range of values is
identified forsome model inputs, these valueswill be randomly sampled when stochastic
simulations are run. The component models of NRAP-Open-IAM are organized into four
major categories:
• Stratigraphy. The stratigraphy component details the structure ofthe GCS system.
Stratigraphy inputs include the numberof shale and aquiferlayers in the model, the
thicknesses of these layers, and the thickness ofthe reservoir.
• Reservoir. The reservoir component describes the conditions in the reservoir during
the simulation time period. NRAP-Open-IAM is nota reservoirsimulator. However,
users can simulate a simplified CO2 injection using the simple and analytical reservoir
components. Inputs for these models include reservoircharacteristics (permeability,
porosity, thickness, extent), C02and brine characteristics (density, viscosity), and
injection rate. More sophisticated reservoirbehaviorcan be included in the NRAP-
Open-IAM by includingsimulation results from a high-fidelitynumerical simulatoras
a look up table.
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• Leakage pathway.The leakage pathway component simulates the upwardflowof CO2
and brine outof the reservoir. NRAP-Open-IAM contains multiple interchangeable
leakage pathway components that can simulate flowthroughcementedand
uncementedwells, seals, and faults. Users must specify the properties of the leakage
pathway, which vary dependingon its type. For example, the inputs forthe cemented
wellbore component are the well radius, the permeability of the well cement, and the
per me ability of potential thief zones.
• Receptor.The receptor componentsimulateseithertheflowofC02and brinein an
aquifer (shallow or deep) or the atmosphere. Aquifer component models consider
geochemical reactions and predict the size of CO 2 and brine impact plumes. A number
of aquifer components exist that re pre sent different types of aquifers (e.g.,
carbonate, deep alluvium). Model in puts for each aquifer component are different
but typically in elude general characteristics of the formation, such as its thickness,
depth, porosity, permeability, and anisotropy.The atmosphere component simulates
COzdispersion after leakage out of the ground. Inputs forthe atmosphere
component include ambient pressure and temperature, wind velocity, CO 2 source
temperature, and coordinates of potential receptors.
Model Output
Outputs are created separately by each component of an NRAP-Open-IAM model:
• Reservoir. The outputsofthe simple and analytical reservoir component models are
the pressure at the top of the reservoir, the CO 2 saturation, and the mass of CO 2 in
the reservoir.
• Leakage pathway. Outputs from each leakage pathway compone nt include CO 2 and
brine leakage rates to any of the specified overlying aquifers.
• Receptor. Outputs for aquifer component mod els typically include impact plume
dimensions (radius in x, y, and z directions) for various metrics including: pH, total
dissolved solids, pressure, and dissolved C02.The atmosphere component model
outputs are flags at receptors indicating whether CO 2 concentrations have exceeded
a pre-defined critical valueandthe critical downwind distance from the source.
Component models in NRAP-Open-IAM are linked so the outputs from one component
can serve as the in puts to another. However, outputs from any component model used in
a simulation can be exported. Simulations in NRAP-Open-IAM are run in either a forward
(one realization) or stochastic (multiple realization (manner. Outputs for all model
realizations can be exported at the end of a simulation.
Risks Behavior
Considered
Leakage risk/containment assurance
Relevant
Permitting Phase
Site Screening, Site Characterization, Injection Operations, Post-Injection Closure
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan, Testing
and Monitoring Plan, Post-lnjectionSite Care and Site Closure Plan, Emergency and
Remedial Response Plan
How the Tool is
Used
NRAP-Open-IAM is generally used in conjunction with a high-fidelity reservoir simulation
software. Outputs from reservoir simulations are brought in to NRAP Open-IAM as lookup
tables and used as a basis for system models that simulate leakage at the site. The tool is
usefulfor: 1) characterizing leakage risks for a proposed injection plan, 2) calculating a
risk-based area of review, 3) justifying the length of a post-injection site care period, and
4) evaluatingvariousriskmitigation plans.
Last Updated
May 2021
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Ongoing
Development
Yes
Ease of Use
NRAP-Open-IAM is written in the widely used Python programminglanguage. Users with
computer programming experience can access the complete functionality of NRAP-Open-
IAM. A graphical user interface is also available for NRAPOpen-IAM that allows users
without computer programming experience to access the base functionality of the code.
Computational
Speed
NRAP-Open-IAM models are comprised of lookup tables, reduced-order models, and
analytical models than can be run concurrently on different processors (in parallel). It was
intentionally designed for computational efficiency to enable the stochastic simulation of
thousands of model realizations.
Tool Verification
The component models of NRAP-Open-IAM have been verified. Details of verification are
provided here: httDs://eitlab.com/NRAP/ODenlAM
Related
References
Bacon, D. H.; Yonkofski, C. M. R.; Brown, C. F.; Demirkanli, D. 1.; Whiting, J. M. Risk-based
post injection site care and monitoring for commercial-scale carbon storage:
Reevaluationof the FutureGen 2.0site using NRAP-Open-IAM and DREAM.
International Journal of Greenhouse Gas Control 2019,90,102784.
Harp, D. R.; Curtis M.Oldenburg, C.M.; Pawar, R. A metricforevaluatingconformance
robustness during geologic C02 sequestration operations. International Journal of
Greenhouse Gas Control 2019,85,100-108.
Lackey, G.; Vasylkivska, V.; Huerta, N.; King,S.; Dilmore, R. (2019), Managing wellleakage
risks at a geologic carbon storage site with many wells. International Journal of
Greenhouse Gas Control2019,88,182-194.
httDs://doi.ore/10.1016/i.iieec.2019.06.011
Vasylkivska,V.; Lackey,G.; Zhang, Y.; Bacon, D.,Chen,B., Mansoor, K.,Yang,Y.; King,S.;
Dilmore, R.; Harp, D. NRAP-Open-IAM: A Flexible Open Source Integrated
Assessment Model forGeologicCarbon Storage RiskAssessmentand
Management. Environmental Modeling & Software 2021,143,105114.
httDs://doi.ore/10.1016/i.envsoft.2 021.105114
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A.10.3 Spatially Integrated Multivariate Probabilistic Assessment (SIMPA)
Tool Name
SIMPA (Spatially Integrated Multivariate ProbabilisticAssessment) Tool
Developer/Owner
National Energy Technology Laboratory
Tool Type
Risk Assessment
Description
SIMPA Tool is a Python-based fuzzy logic tool designed to help assess the likelihood of
fluid and/or gas migration pathways throughout the subsurface. The SIMPAtool helps
users develop and apply fuzzy logic to various datasets to construct knowledge-based
inferential rules that reduce uncertainty and results in a visual representation depicting
the likelihood of potential flu id and/or gas migration pathways. SIMPA results spatially
describe the potential magnitudeand extent of natural and anthropogenicsubsurface
pathways, for areas with little or no data, to help evaluate potential subsurface hazards
to improve storage assessments and critical information for improving industrydecisions
related to the use of various CCS methods and technologies.
Tool Licensingand
Access
Creative Commons Attribution - available for download on EDX.
httDs://edx.netl.doe.eov/dataset/simDa-tool
Model Input
Any number of raster ized coverage layers associated with surface or subsurface risks and
hazards
One or more sets of fuzzy logic rules (can be authored in tool)
One or more sets of combinatorial/output rules (can be authored in tool)
Any number of output raster layers, whose composition and count are dependent on the
fuzzy logic and output rules applied
Model Output
An output raster recording the number of no-data values found at a given pixel
coordinate
A .csv containing the above information in a tabular form
Risks Behavior
Considered
Tool helps identify areas with high structural complexity and a greater likelihood for
leakage pathways. This information can aid in planning and permitting efforts, as well as
support human health and environmental riskmitigation efforts.
Relevant
Permitting Phase
Primarily designed for site screening, butwith additional information could supportsite
characterization and post-injection
Class VI Permit
Element
Addressed
Site Characterization, Site Characterization, Area of Review and Corrective Action Plan,
Testingand Monitoring Plan, Post-Injection Site Care and Site Closure Plan
How the Tool is
Used
Tool could be used to understand risks associated with geologic structure (faults,
fractures, formation thickness and extents), water resources (aquifers, water wells), and
legacy oil and gas well infrastructure
Last Updated
April 16,2020
Ongoing
Development
The tool has limited support for addressing minor issues. Current usercommunity is
predominately within DOE.
Ease of Use
A graphical user interface is offered, along with tool support to help users determine and
setfuzzy logic inferential rulesto produce model outputs. Experience with geospatial
data, especially raster data formats is preferred.
Computational
Speed
SIM PA's processing steps are SIM D-style algorithms and are designed to be run on any
number of threads and CPU cores in parallel. The performance increases dramaticallyas
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the number of pixels gets larger when compared to running serially. For a problem with
27,335 pixels, the average parallel runtakes undera minute on the same hardware
where a serial/single-threaded version takes over 10 minutes to run.
Theoretically, there may be computational speed limits, but they have not been hit yet.
Tool Verification
The fuzzy logic portionshave been tested enoughfor confidence in its use. The tool is
general purpose enough thatscenario-specificvalidation will depend on the data being
used,and the rulesbeingapplied.
Related
References
SIMPA Tool: httDs://edx.netl.doe.eov/dataset/simDa-tool
SIMPA Publication:
httDs://www.sciencedirect.com/science/article/Dii/S019181412 0300857
Use case datasets: structural and wellbore:httDs://edx.netl.doe.eov/dataset/oklahoma-
structural-comDlexitv-data
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A.10.4 The Evidence Support Logic Application (TESLA)
Tool Name
The EvidenceSupport LogicApplication (TESLA)
Developer/Owner
Quintessa
Tool Type
Risk Assessment
Description
The technique of EvidenceSupport Logic implemented in Quintessa's TESLA software is
intended to support decision-makers and modelers in their sense-making when faced
with extensive information processing requirements. In summary, evidence support logic
involves systematically breaking down the question or hypothesis under consideration
into a logical hypothesis model the elements of which expose basicjudgments and
opinions relating to the quality of evidence associated with a particularinterpretation or
proposition, in addition to establishingthe level of confidence that can be placed in the
relevant judgments. By independently evaluating confidence "for" and "against"
propositions on the basis of evidence, uncertainty(and/orconflict) is captured and the
sensitivity of the results to that uncertainty can be evaluated.
Tool Licensingand
Access
Commercial:
httDs://www.auintessa.ore/software/downloads-and-demos/tesla-2.1.1
Model Input
A logical hypothesis model, sources of evidence forthese hypotheses, uncertainty
Model Output
Confide nee in the inputted hypotheses (Ratio plot, Tornado plot, Tree display, Flow lines)
Risks Behavior
Considered
Leakage, storage resource, faults, fractures, and any other risks at a GCS site that a user
defines
Relevant
Permitting Phase
Site screening, site characterization
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan,
Financial Assurance Demonstration, Emergencyand Remedial Response Plan
Last Updated
2012
Ongoing
Development
Maintained by Quintessa
Related
References
httDs://www.auintessa.ore/software/downloads-and-demos/tesla-2.1.1
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A. 11 SEISMIC AND GEOMECHANICAL RISK
Underground injection of C02 causes a pressure increase that can increase the risk of triggering
seismic events or inducing fractures in existing formations. Tools in this category are used to
characterize the seismic and geomechanical risks associated with underground CO2 injection.
A. 11.1 Athena Data Management
Tool Name
Athena Data ManagementSystem
Developer/Owner
Nanometrics
Tool Type
Seismic and Geomechanical Risk
Description
The Athena Data ManagementSystem allows one to browse up-to-date event
catalogues, view all recorded event source parameters and waveforms, select and
download sections of the catalogue, plot frequency/magnitude relationships for event
clusters, examine maps showing distribution of ground motions from each recorded
event and track networkseismicity rate to manage risks associated with induced
seismicity in realtime. It is integrated with real-time monitoring that tracks probabilistic
estimates of future maximum magnitude and seismicity rate.
Tool Licensingand
Access
Commercial: Contact Nanometrics at httDs://www.nanometrics.ca/services/passive-
seismic-monitorine/athena-data-manaeement-svstem
Open-source version called ORION being developed as part of NRAP and SMART
Model Input
High-precision catalog of seismic events, magnitudes, injection rate
Model Output
Short-term seismic hazard assessment
Risks Behavior
Considered
Seismic Hazard
Relevant
Permitting Phase
Monitoring plan and risk mitigation
Class VI Permit
Element
Addressed
Testingand Monitoring Plan, Emergency and Remedial Response Plan, Stimulation
Program
How the Tool is
Used
It is a service that is provided to operators. The operator is given a link to look at the
dashboard, but the re is no ability for users to "interact" or change properties.
Ongoing
Development
Yes
Ease of Use
Comes with a graphical user interface. Programming skills may not be needed to learn
the software.
Computational
Speed
It is reasonablyfastand near real time
Related
References
httDs://www.nanometrics.ca/service s/Dassive-seismic-monitorine/athena-data-
manaeemen t-svstem
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A.11.2 Fault Slip Potential
Tool Name
FaultSlip Potential
Developer/Owner
Stanford Centerforlnducedand Triggered Seismicity and Exxon Mo bil/XTO
Tool Type
Seismic and Geomechanical Risk
Description
Fault slip potential (FSP) is a software to predict the probability of fault slip to occur in
response to pore pressure increase dueto injection.
Tool Licensingand
Access
Get added to the mailing list and follow instructions for downloading:
httDs://scits.stanford.edu/software
Model Input
Stress model (stressgradients, or A-phi model parameters), fault interpretation
(location, length, strike, kinematics), hydro logical model (reservoir thickness, porosity,
permeability, or user defined model specifying pressure increase), injection well
specifications (location, injection volume), uncertainty(distributionof the parameters)
Model Output
Probability of faults to slip
Risks Behavior
Considered
Seismic risk
Relevant
Permitting Phase
Site screening, Pre-injection, Monitoring
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Testing and Monitoring Plan, Stimulation Program
How the Tool is
Used
See description above
Ongoing
Development
Yes
Ease of Use
Comes with a graphical user interface. Programming skills may not be needed to learn
the software.
Related
References
Walsh, F. R.; Zoback, M. D. Probabilistic assessment of potentialfault slip related to
injection-induced earthquakes:Applicationto north-central Oklahoma, USA.
Geoloav 2016.44.991-994. doi: httDs://doi.ore/10.1130/G38275.1
httDs://scits.stanford.edu/software
httDs://scits.stanford.edu/file/fullmeetinevideomD4
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A.11.3RiskCat
Tool Name
RiskCat
Developer/Owner
Bill Foxall and Jean Savy
Tool Type
Seismic and Geomechanical Risk
Description
RiskCatdeterminesthe seismic hazard and riskbasedon seismiccatalogs. RiskCatuses
SynHaz to determine the ground motion internally to determine the risk at a specified
location.
Tool Licensingand
Access
The tool is available on eitlab: httDs://eitlab.com/NRAP/RiskCat
Model Input
Seismic catalogs (timing, magnitude, location) and seismic source parameters if possible
Model Output
Hazard and risk curves, i.e., probabilities of exceeding certain values of accelerations or
risk values
Risks Behavior
Considered
Seismic hazard and risk
Relevant
Permitting Phase
With simulated catalogs, the tool can be used during the site screening. With recorded
catalogs, the tool can determine the increase of hazard and riskduringthe injection and
post-injection.
Class VI Permit
Element
Addressed
Site Screening, Post-Injection Site Care and Site Closure Plan, Emergencyand Remedial
Response Plan
How the Tool is
Used
With simulated catalogs, the tool can be used during the site screening. With recorded
catalogs, the tool can determine the increase of hazard and riskduringthe injection and
post-injection.
Last Updated
It was uploaded to GitLab in 2020
Ongoing
Development
Sup port for the tool exists in theory, but it is not always straightforward
Ease of Use
Basic knowledge of seismic catalogs and risk calculations are needed to run the tool.
Knowledge of how to manipulate in put files is needed.
Computational
Speed
Model is not optimized for speed
Tool Verification
No
Related
References
Gitlab includes a manual: httDs://eitlab.com/NRAP/RiskCat
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A.11.4 RSOSim
Tool Name
RSQSim
Developer/Owner
James H. Dieterich and Keith Richards-Dinger at UC Riverside
Tool Type
Seismic and Geomechanical Risk
Description
RSQsim is 3D boundary-element code incorporating rate-state fault friction to simulate
longsequencesof earthquakesin interactingfault systems. It can simulate seismic
events based on the interaction of tectonic loading, stress changes due to earthquake
occurrence, and external pressure and/or stress histories (e.g., those that arise from
anthropogenicsources).The external pressure and/or stress histories must be calculated
extern ally and provided to RSQSim by means of an addition in put file containing the
pressure and/or stress for every fault element as a function of time.
Tool Licensingand
Access
Agithub distribution is in the works. It is currently not publicly available, only through
contact with the developers.
httDs://Drofiles.ucr.edu/iames.dieterich
httDs://Drofiles.ucr.edu/aDD/home/Drofile/keithrd
Model Input
The primary input parameters: Fault constitutive/material parameters (including rate-
state parameters, absolute shear and normal stresses, elastic moduli, a fault model, and
long-term average slip rates for all fault elements). In the simplest form, a fault file
should contain the x, y, z location of the centers of the fault elements, strike, dip, rake,
and slip rate for each element. The RSQSim source code in eludes scripts to pre pare fault
models based on standardized input in the UCERF3 fault model format (based on fault
surface trace information) or planarfault structures (including those with fractal
roughness orsegmentation). Faults can be discretized into rectangular to triangular
elements that better represent surfaces with complex geometries. RSQSim also accepts
spatially variable constitutive and/or material parameters provided via an in put file with
a value for each fault element. External pressure and/or stress histories should be
providedin a similar fashion.
Model Output
RSQSim producesa seismic catalogwith occurrence times, magnitudes, rupturearea,
stress drop, event location, seismic moment, and slip per fault element. Additional
information is also provided for the entire fault system at user-specified intervals. This
information includes the shear and normal stress, slip speed, and slip-state evolution.
Risks Behavior
Considered
Induced and natural seismicity hazard estimation
Relevant
Permitting Phase
Site screening, pre-injection, operational management
Class VI Permit
Element
Addressed
Site Screening, Post-Injection Site Care and Site Closure Plan, Emergencyand Remedial
Response Plan,Stimulation Program
How the Tool is
Used
RSQSim uses site-specific (local and/or basin-scale) reservoir, flow, material, fault
location/geometry, and constitutive parametersand external pressure/stress history to
compute the seismicresponseto the operation.
Last Updated
RSQSim is actively undergoing development
Ongoing
Development
RSQSim is actively undergoing development
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Ease of Use
The installation of the tool and the tool itself require programmingskills. RSQSim is run
on the command line or can be executed through user-generated wrappers in their
preferred programming language. Built-in postprocessing scripts are written in R.
RSQSim requiresexpert-level user knowledge.
Computational
Speed
Computational costs scale with the number of fault elements. RSQSim is highly-
parallelized (via openMPI) and optimized to run on super-computer platforms.
Tool Verification
httDs://Dubs.eeoscienceworld.ore/ssa/srl/article-abstract/83/6/9 83/315277/RSQSim-
Earthauake-Simulator
Related
References
httDs://Dubs.eeoscienceworld.ore/ssa/srl/article-abstract/83/6/9 83/315277/RSQSim-
Earthauake-Simulator
Kroll, K. A.; Cochran, E.S. Stress Controls Rupture Extend and Maximum Magnitude of
Induced Earthquakes. Geophysical Research Letters 2021. DOI:
10.1029/2020GL092148.
Kroll, K. A.; Buscheck, T. A.; White, J. A.; Richards-Dinger, K. B.Testingthe Efficacy of
Active Pressure Management as a Tool to Mitigate Induced Seismicity.
International Journal of Greenhouse Gas Control 2019.
Kroll, K. A.; Richards-Dinger, K. B.; Dieterich, J. H. 2017. Sensitivity of Induced Seismic
Sequences to Rate-and State- Frictional Processes .Journal of Geophysical
Research: Solid Earth 2017,122.
Dieterich, J. H.; Richards-Dinger, K. B.; Kroll., K. A. Modeling Injection- induced Seismicity
With the Physics-based Earthquake Simulator RSQSim. Seismological Research
Letters 2015,86,1102-1109.
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A. 11.5 Seismogenic Index Model
Tool Name
Seismogenic Index Model
Developer/Owner
The theory is developed by Shapiro and collaborators. Codes for the model have been
developed by different people.
Tool Type
Seismic and Geomechanical Risk
Description
Seismogenic index characterizes the seismic response of a rock to a unit volume of
injected fluid. It has been used by Nanometrics in their Athena Seismicity Portal and in
various publications demonstrating the on-going hazard evolution in areas like
Oklahoma
Tool Licensingand
Access
Open-source: httDs://eithub.com/amienan/rseismTLS
httDs://eith ub.com/RvanJamesSchultz/Seismoeeniclndex
Model Input
Seismic catalog and an injection rate
Model Output
Estimate of short-term forecast of the number of seismic events and seismic hazard
Risks Behavior
Considered
Seismic Hazard
Relevant
Permitting Phase
Monitoring plan and risk mitigation
Class VI Permit
Element
Addressed
Site Screening, Post-Injection Site Care and Site Closure Plan, Emergencyand Remedial
Response Plan,Stimulation Program
How the Tool is
Used
Requiresexpertuserinteraction with Rand/orMATLAB
Last Updated
The Github accounts listed above were last updated in 2020and 2018, respectively
Ongoing
Development
Unknown
Ease of Use
Code is in Ror Matlab, some level of programming experience would be needed
Computational
Speed
Can be run in real-time, provided that a good seismicity catalog exists
Tool Verification
There are publicationson the model, notsureabouttool implementation.The github
site has some readme files about the code.
Related
References
Shapiro, S. A.; Dinske, C.; Langenbruch, C.; Wenzel, F. Seismogenic index and magnitude
probability of earthquakes induced during reservoir fluid stimulations. The
Leadina Edae 2010.29.304-309. doi: httDs://doi.ore/10.1190/1.3353727
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A.11.6 Short-Term Seismic Forecasting Tool (STFS)
Tool Name
Short-Term Seismic Forecasting Tool (STSF)
Developer/Owner
Corinne Layland-BachmannatLBNL
Tool Type
Seismic and Geomechanical Risk
Description
The Short-Term Seismic Forecasting (STSF)tool uses site-specific catalogs of measured
seismicity to fore cast future event frequency over the short term. The STSF tool uses a
model developed for the decay of aftershocks of large seismic events to determine the
event rate in future time bins. This mode lis adapted with a term to modify the
background seismicity rate above a pre-determined magnitude threshold as a function
of injection-related parameters (e.g., injection rate or bottom-hole pressure). This
injection-relatedseismicityforecastingcapability can be a valuable tool to complement
stoplightapproachesfor induced seismicity risk planningand permitting.
Tool Licensingand
Access
Tool is available on EDX: httDs://edx.netl.doe.eov/nraD/short-term-seismic-forecastine-
stsf/
Model Input
Seismic catalog (timing and magnitude at a minimum), injection parameter (such as
injection rate, downhole pressure, etc.)
Model Output
Seismicity rates for given time and magnitude bins
Risks Behavior
Considered
Induced seismicity
Relevant
Permitting Phase
Injection, post-injection
Class VI Permit
Element
Addressed
Testingand Monitoring Plan, Stimulation Program
How the Tool is
Used
Aid decision-making during active injection
Last Updated
2018
Ongoing
Development
Tool is being integrated into a biggerdashboard, tool is still being supported, tool has
active users
Ease of Use
Tool runs as a graphical user interface, but only on Linux and Mac computers. Can be
used with a pearl scriptfor moreadvancedusers.
Computational
Speed
Speed is not optimized. Steps can take from seconds to minutes and a whole simulation
depends on the problem size.
Tool Verification
Not the tool, butthe method has been verified in Bachmann etal. (2011)
Manual: httDs://edx.netl.doe.eov/dataset/short-term-seismic-forecastine-stsf-reduced-
order-model-rom-tool-users-euide-version-2 016-11-1-0-4
Related
References
Bachmann, C. E.; Wiemer, S.; Woessner, J.; Hainzl, S. Statistical analysis of the induced
Basel 2006 earthquake sequence: introducing a probability-based monitoring
approach for Enhanced Geothermal Systems. Geophysical Journal International
2011,186,793-807.
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A.11.7 State of Stress Analysis Tool (SOSAT)
Tool Name
State of Stress Analysis Tool (SOSAT)
Developer/Owner
NRAP/PNNL/Jeff Burghardt
Tool Type
Seismic and Geomechanical Risk
Description
The State of Stress Analysis Tool (SOSAT) is a Python package that helps analyze the state
of stress in the subsurface using various typesof commonly available characterization
data such as well logs, well test data such as leakoff and minifractests, regional geologic
information, and constraints on the state of stress imposed by the existence of faults and
fractures with limited frictional shear strength. It employs a Bayesian approach to
integrate these data into a probability density function for the principal stress
components.
Tool Licensingand
Access
The tool is publicly available. The re is a version with a GUI accessible at:
httDs://edx.netl.doe.eov/nraD/state-of-stress-analvsis-tool-sosat/
And there is an open-source Pvthonlibrarv available at: httDs://eithub.com/Dnnl/SOSAT
The Python library has more features, but currently no graphical user interface.
Model Input
Well logs, well tests, regional stress observations
Model Output
Probability distribution for the state of stress at a point in the subsurface, as well as a
probability estimate for the risk of hydraulic fracturing or fault activation at a point as a
function of pore pressure
Risks Behavior
Considered
Leakage by hydraulicfracturingorfaultslip in sealing formations, and induced seismicity
Relevant
Permitting Phase
ClassVI site characterizationand injection
Class VI Permit
Element
Addressed
Site Characterization, Stimulation Program
How the Tool is
Used
The tool would be used to assemble all geomechanical characterization data for a site into
a probabilistic estimate of the state of stress, which can then be used to estimate the
probability of tensile or shear failure of caprock, which can be used to determine the
maximum safe injection pressure. The tool could also be used to evaluate probability of
fault activation, on known faults or on an assumed unknown critically oriented fault,
which is useful for evaluatingthe riskof induced seismicity.
Last Updated
The GitHub site hosts a development branch and tagged releases. The repository has a set
of quality control checks that are evaluated with every update and new tests are regularly
written as new features are added. The last tagged release was April 26,2021.
Ongoing
Development
The tool is still under active development. There is a user community forum on the NETL
EDXsite,and support from the developeris available.
Ease of Use
The graphical user interface version has fewer features, but it has a user's manual with
examples and a description of how to choose inputs and use outputs. The user would
need some level of familiarity with geology and geomechanics, but not expert level
knowledge. The GitHub Python libraryhas documentation and examplesbutrequiresa
basic level of familiarity with Python.
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Computational
Speed
The calculations at each point only take a few minutes. With the Python library it is
possible to construct depth profiles and 2D maps, in this case each spatial location
requiresafewminutessothatcalculationscouldtake an hour orso.
Tool Verification
There are continuous integration tests thatcheckaccuracy and consistency of results as
the tool is updated. A few of these compare against analytical solutions, but in other cases
where statistical sampling techniques (rejection sampling, Markov Chain Monte Carlo) are
used there are no analytical solutions, so the tests checkfor changes in the results
introduced by code modifications.
Related
References
Appriou, D. Assessment of the geomechanical risks associated with CO 2 injection at the
FutureGen 2.0Site; PNNL-28657; Pacific Northwest National Laboratory,
Richland. WA. 2019. httDs://www.Dnnl.eov/Dublications/assessment-
eeomechanical-risks-associated-co2-iniection-futureeen-20-site
Burghardt,J. A.; Appriou, D. State ofStress Uncertainty Quantification and Geomechanical
Risk Analysis for Subsurface Engineering. In Proceedings of the 55st US Rock
Mechanics/GeomechanicsSymposium; paper number ARMA-2021-2129;2021.
httDs://oneDetro.ore/ARMAUSRMS/Droceedines-abstract/ARMA21/AII-
ARMA21/ARMA-2021-2129/468335
Burghardt, J. Geomechanical Risk Assessment for Subsurface Fluid DisposalOperations.
Rock Mechanics and Rock Engineering 2018,51, 2265-2288.
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A.12 WELL TEST AND LOG INTERPRETATION
A variety of well logging and testing techniques exist that provide insight into the characteristics
of subsurface formations. Tools in this category are used to interpret and organize diverse well
testing and logging information.
A.12.1 IHS WellTest
Tool Name
IHS WellTest
Developer/Owner
IHS/Fekete
Tool Type
WellTestand Log Interpretation
Description
Software for conductinggas and oil pressure transientanalysisand servesas an everyday well
test data interpretation tool
Tool Licensingand
Access
Commercial license:
httDs://ihsmarkit.com/Droducts/wellte st-reserve-Dta-software.html
Model Input
Well test pressure, flow rates, reservoir information
Model Output
Reservoir parameters, permeability, porosity, transmissivity, reservoir features, injection
pressures
Risks Behavior
Considered
Injectivity, leakage, storage resource, faults, fractures, boundaries
Relevant
Permitting Phase
Site characterization, monitoring, operations, closure
Class VI Permit
Element
Addressed
Site Characterization, Area of Review and Corrective Action Plan, Financial Assurance
Demonstration, Well Construction Details, Testing and Monitoring Plan, Injection Well
Plugging Plan, Post-Injection Site Care and Site Closure Plan
Last Updated
Routine updates
Ongoing
Development
Commercial, regularupdates
Related
References
httDs://ihsmarkit.com/Droducts/wellte st-reserve-Dta-software.html
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A.12.2 Interactive Petrophysics (IP)
Tool Name
Interactive Petrophysics (IP)
Developer/Owner
Lloyd's Register. Starting in 1760, Lloyd's Register is one of the world's leading providers
of professional services for engineering and technology.
Tool Type
WellTestand Log Interpretation
Description
IP offers a complete, cost-effective industry-standard solution to detailed formation
evaluation (porosity, permeability, capillary pressure, fluid saturation, and volumetrics)
using deterministic, probabilistic, and machine learning approaches. IP is a very popular
petrophysical data processing and interpretation software in the energy industry. It is
robust, stable, and user-friendly. It is fully customizable and external codes (e.g., Python)
can be imported into it. As per IP website, it is used in >85 countries by >500companies
and >107 universities.
Tool Licensingand
Access
Lloyd's Register. Commercial license:
httDs://www.lr.ore/en-us/iD-well-analvsis-software/
Model Input
Any kind of open hole and cased hole wireline logs, logging-while-drilling logs, rock core
data (porosity, permeability, saturation, geomechanics), core images, and previous user
interpretations, etc. It offers analysis of pore pressure, wellbore stability, casing and
cement quality, and live analysis of wellsite log data.
Model Output
Robust multi-well processing and interpretation, and customizable visualization of
formation lithology, clay volume, total porosity, effective porosity, fluid saturation,
geomechanical properties, rock physics,fractures, saturation height, and uncertainties. IP
offers Monte Carlo simulationfor reservoir properties used in volumetricscalculation. In
addition, IP's machine learning module offers classification of rock types and prediction of
missing curves.
Risks Behavior
Considered
Monte Carlo simulation of uncertainty analysis of rock and fluid properties
Relevant
Permitting Phase
Site screening (very relevant), site characterization (very relevant), injection, post-
injection
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan
How the Tool is
Used
User imports petrophysical log and core data and analyzes the caprockand reservoir
properties in both deterministic and probabilistic approaches. The derived properties are
then used in volumetriccalculations.The tool also providesTornadochartsshowingthe
sensitivities of all model input.
Last Updated
2021
Ongoing
Development
The tool is robust and stable. The company regularly updates the software with new
modules and approaches.
Ease of Use
The tool has a user-friendly graphical user interface (including ID, 2D, and 3Dplots).The
usersdo notneedanycomputerprogramming skills. Interestedand advanced users can
import their codes (e.g., Python) into this software and runtheirown algorithms for
1,000s of wells. It offers 24/7 customer support.
Computational
Speed
IP is very fast, and it does not take more than a few seconds for advanced petrophysical
analysis.
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Tool Verification
Results are compared with rockcore data inside and outside the software and published
in peer-reviewed literature.
Related
References
httDs://www.lr.ore/en-us/iD-well-analvsis-software/
httDs://www.voutube.com/watch?v=mmc5TF6L3 KOfficialYouTube videos of IP)
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A.12.3 Neuralog
Tool Name
Neuralog
Developer/Owner
Neuralog Pro
Tool Type
WellTestand Log Interpretation
Description
NeuraLog transforms scanned images into usable digital data.
Tool Licensingand
Access
httDs://www.ne uraloe.com/well-loe-dieitizine-software-neuraloe/
httDs://www.ne uraloe.com/reauest-license/
Model Input
Raster well logs-Standard color, grayscale or b/w TIFF, JPEG, PDF or BMP image
Model Output
LAS1.2; LAS2.0 (Log ASCII Standard) - d igital logcurvedata
AutoCAD DXF; IHS PETRA ASCII Well Data; Tab Delimited ASCII
Risks Behavior
Considered
No risks or behaviors
Relevant
Permitting Phase
Site screening, site characterization
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Reviewand Corrective Action Plan
How the Tool is
Used
NeuraLog creates straightened and depth-registered digital imagesfor geological
applications. The software includes a comprehensive set of tools such as automated curve
tracing, lithology data capture, interactive log display, image warp and stretch correction
to improve the quality of digital logdata.
Last Updated
January 31,2020
Ongoing
Development
It has an active user community; support for the tool is available
Ease of Use
Operating system Windows 7/8/10; no need for computer programming skillsto use the
tool
Computational
Speed
The model is designed for computational efficiency
Related
References
httDs://www.neuraloe.com/Droduct brochures/Neuraloe-Products-Solutions.Ddf
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Rules and Tools Crosswalk
A.12.4 Strater
Tool Name
Strater
Developer/Owner
Golden Software
Tool Type
WellTestand Log Interpretation
Description
Visualize and analyze subsurface data as well logs, boreholes, and cross sections
Tool Licensingand
Access
Commercial: httDs://www.eoldensoftware.com/Droducts/strater
Model Input
Well log information, LAS files, well specifications
Model Output
Borehole logs, well designs, geologic cross sections
Risks Behavior
Considered
Well integrity, geohazards, geologic variability
Relevant
Permitting Phase
Site screening, site characterization
Class VI Permit
Element
Addressed
Site Screening, Site Characterization, Area of Re vie wand Corrective Action Plan, Well
Construction Details, Injection Well Plugging Plan, Post-Injection Site Care and Site Closure
Plan
Last Updated
Version 5.7.1094.
Ongoing
Development
Commercial, regularupdates
Related
References
httDs://www.eoldensoftware.com/Droducts/strater
A-92
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Rules and Tools Crosswalk
A.12.5 Techlog
Tool Name
Techlog
Developer/Owner
Schlumberger
Tool Type
WellTestand Log Interpretation
Description
Incorporates data acquired from near-wellbore environments (e.g., geophysicalwell logs,
core data, etc.) to assist users in performing petrophysical analyses and geologic
interpretation tasks.
Tool Licensingand
Access
Commercial proprietary software. Licensing options purchased via communication with
Schlumbereer. httDs://www.software.slb.com/Droducts/techloe
Model Input
Geophysicalwell log data, core data, geologic formation tops, and wellhead data
Model Output
Synthetic geophysicalwell log data, well correlations, graphics, and interpretations
Risks Behavior
Considered
Parameter uncertainty/sensitivity analysis
Relevant
Permitting Phase
Site screening, site characterization, and application preparation
Class VI Permit
Element
Addressed
Site Screening, Site Characterization
How the Tool is
Used
Techlogcan be used to evaluateand interpretwellboreinformation in the nearbyregion
after collecting site-specific data and to create inputs for 3D geologic modeling. It can also
be used to generate figures for reporting/permit application activities.
Last Updated
June 30,2021 (latest major release)
Ongoing
Development
Schlumberger develops, supports, and maintains the software. It is a standard tool in the
oil and gas industry.
Ease of Use
The tool has an interactive graphical user interface. No programming skills are required,
but Python can be utilized in Techlog workflows. Well log interpretation experience is
recommended before use.
Computational
Speed
Petrophysical modeling can generate loads of varying sizes on computational resources.
Machine learning and data analysis tasks performed with the software could potentially
lead to long computational times. Basic tasks (loading well logs, viewing well logs, basic
interpretation/analysis) are generally not computationally intensive.
Tool Verification
The tool has been used forseveral years throughoutthe oil and gas industry.
Related
References
httDs://www.software.slb.com/Droducts/techloe
httDs://www.software.slb.com/Droducts/Droduct-library-
v2?Droduct=Techloe&tab=Case%20Studies
A-93
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Rules and Tools Crosswalk
A. 13 WELL DESIGN
Class VI wells must be appropriately designed to handle the proposed C02 injection. Tools in
this category are primarily used to aid well design (e.g., sizing of casings).
A.13.1 PIPESIM
Tool Name
PIPESIM
Developer/Owner
Schlumberger
Tool Type
Well Design
Description
PIPESIM is a steady state multi-phase flow simulator used for designing wells, pipelines, or
a network of we lis and pipelines. The tool incorporates flow modeling, heat transfer, and
fluid behaviorto help size and optimize welland pipelinesystems.
Tool Licensingand
Access
It can be downloaded from Schlumberger Information Solutions (SIS) website. License
needs to be purchased from SIS. httDs://www.software.slb.com/Droducts/DiDesim
Model Input
Pressure boundary conditions (start and/or end), reservoir properties (porosity, depth,
permeability, skin, etc.), fluid flow rates
Model Output
Bottomhole pressure vs. depth for various tubing-casing programs, pipeline diameter and
length dependingon flowratesand terrain, fluid mass/temperature/phase streams
between networkcomponents (wells/pipelines)
Risks Behavior
Considered
BHP modeling can potentiallyand indirectly be usedto understand risk of over pressuring
the formation (seismicity)
Relevant
Permitting Phase
Site screening, feasibility study, design/FEED, permitting
Class VI Permit
Element
Addressed
Site Screening, Well Construction Details, Injection Well Plugging Plan
Last Updated
2020
Ongoing
Development
The tool is commercially available and widely used
Related
References
Technical PaDers - httDs://www.software.slb.com/Droducts/Droduct-librarv-
v2?Droduct=PIPESIM&tab=Technical%20PaDers
Case Studies - httDs://www.software.slb.com/Droducts/Droduct-librarv-
v2?Droduct=PIPESIM&tab=Case%20Studies
A-94
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NRAP
National Risk Assessment Partnership
NRAP is an initiative within DOE's Office of Fossil Energy and is led by the National Energy
Technology Laboratory (NETL). It is a multi-national-lab effort that leverages broad technical
capabilities across the DOE complex to develop an integrated science base that can be applied to
risk assessment for long-term storage of carbon dioxide (C02). NRAP involves five DOE
national laboratories: NETL, Lawrence Berkeley National Laboratory (LBNL), Lawrence
Livermore National Laboratory (LLNL), Los Alamos National Laboratory (LANL), and Pacific
Northwest National Laboratory (PNNL).
Technical Leadership Team
Diana Bacon
Task Lead, Risk Assessment Tools and Methods
Field Validation
Pacific Northwest National Laboratory
Richmond, WA
Rajesh Pawar
LANL Team Lead
Task Lead, Containment / Leakage Risk
Los Alamos National Laboratory
Los Alamos, NM
Chris Brown
PNNL Team Lead
Pacific Northwest National Laboratory
Richmond, WA
Abdullah Cihan
LBNL Team Co-Lead
Lawrence Berkeley National Laboratory
Berkeley, CA
Robert Dilmore
Technical Director, NRAP
Research and Innovation Center
National Energy Technology Laboratory
Pittsburgh, PA
Erika Gasperikova
Task Lead, Strategic Monitoring
LBNL Team Co-Lead
Lawrence Berkeley National Laboratory
Berkeley, CA
Kayla Kroll
Task Lead, Induced Seismicity Risk
Management
Lawrence Livermore National Laboratory
Livermore, CA
Tom Richard
Deputy Technical Director, NRAP
The Pennsylvania State University
State College, PA
Megan Smith
LLNL Team Lead
Lawrence Livermore National Laboratory
Livermore, CA
Brian Strazisar
NETL Team Lead
Research and Innovation Center
National Energy Technology Laboratory
Pittsburgh, PA
R. Burt Thomas
Task Lead, Addressing Critical Stakeholder
Questions
Research and Innovation Center
National Energy Technology Laboratory
Albany, OR
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U.S. DEPARTMENT OF
ENERGY
National Risk Assessment Partnership
Brian Anderson
Director
National Energy Technology Laboratory
U.S. Department of Energy
Bryan Morreale
Associate Laboratory Director for
Research & Innovation
Research & Innovation Center
National Energy Technology Laboratory
U. S. Department of Energy
NRAP Executive Committee
Grant Bromhal
Senior Research Fellow
Geological & Environmental Systems
National Energy Technology Laboratory
Jens Birkholzer
Associate Laboratory Director
Energy tunc! Environmental Sciences
Lawrence Berkeley National Laboratory
Mark Ackiewiez
Director
Office of Carbon Management
Technologies
Office of Fossil Energy and Carbon
Management
U. S. Department of Energy
John Litynski
Director
Division of Carbon Transport & Storage
Office of Fossil Energy and Carbon
Management
U.S. Department of Energy
Darin Damiani
Carbon Storage Program Manager
Division of Carbon Transport and
Storage
Office of Fossil Energy and Carbon
Management
U.S. Department of Energy
George Peridas
Director, Carbon Management
Partnerships
Lawrence Livermore National
Laboratory
Melissa Fox
Program Manager
Applied Energy Programs
Los Alamos National Laboratory
George Guthrie
Chair, NRAP Executive Committee
Program Manager
Earth and Environmental Sciences
Los Alamos National Laboratory
F rederick Day-Lewis
Laboratory Fellow, Chief Geophysicist
Earth System Sciences
Pacific Northwest National Laboratory
Mark McKoy
Carbon Storage Technology Manager
NEIL Office of Science and
Technology Strategic Plans and
Programs
National Energy Technology Laboratory
U.S. Department of Energy
N=
TL
NATIONAL
ENERGY
TECHNOLOGY
LABORATORY
• Los Alamos
NATIONAL LABORATORY
Pacific
Northwest
NATIONAL
LABORATORY
NRAP Technical Report Series
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