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NRAP-Open-IAM: FutureGen2 Component Models

Bacon D. H. NRAP-Open-IAM: FutureGen2 Component Models, 2021. PNNL-31781. Richland, WA: Pacific Northwest National Laboratory. https://www.osti.gov/servlets/purl/1825928

Fostering Data Curation Throughout the Entire Carbon Storage Data Life Cycle via the Energy Data eXchange and GeoCube

Morkner, P., Bauer, J., Rose, K., Rowan, C., Barkhurst, A. (2021, July 27). Fostering Data Curation Throughout the Entire Carbon Storage Data Life Cycle via the Energy Data eXchange and GeoCube. [Conference presentation]. Invited talk at the CCUS Database Virtual Symposium. https://www.osti.gov/servlets/purl/1844394

Influence of Effective Stress and Transport on Mechanical and Chemical Alteration Processes at the Cement-Caprock Interface

Rhino, K.; Iyer, J.; Walsh, S. D. C.; Carroll, S. A.; Smith, M. M. Influence of Effective Stress and Transport on Mechanical and Chemical Alteration Processes at the Cement-Caprock Interface. International Journal of Greenhouse Gas Control 2021,109, Article 103340. https://www.sciencedirect.com/science/article/pii/S175058362100092X?via%3Dihub

NRAP-Open-IAM: Open Wellbore Component v2.0

Bacon D. H.; Pan, L.; Oldenburg, C. M. NRAP-Open-IAM: Open Wellbore Component v2.0, 2021. PNNL-31543. Richland, WA: Pacific Northwest National Laboratory. https://doi.org/10.2172/1825929

Stress Controls Rupture Extent and Maximum Magnitude of Induced Earthquakes

Kroll, K. A.; Cochran, E. S. Stress Controls Rupture Extent and Maximum Magnitude of Induced Earthquakes. Geophysical Research Letters 2021, 48(11), e2020GL092148. https://doi.org/10.1029/2020GL092148

AI/ML Forecasting of Offshore Platform Integrity to Improve Safety and Reliability

Romeo, L., Dyer, A., Bauer, J., Barkhurst, A., Duran, R., Nelson, J., Sabbatino, M., Wenzlick, M., Wingo, P., Zaengle, D. and Rose, K. 2021. Forecasting Offshore Platform Integrity: Applying Machine Learning Algorithms to Quantify Lifespan and Mitigate Risk. Machine Learning in Oil & Gas. April 15, 2021. Virtual. https://www.osti.gov/servlets/purl/1845120

Forecasting Offshore Platform Integrity: Applying Machine Learning Algorithms to Quantify Lifespan and Mitigate Risk

Romeo, L., Dyer, A., Bauer, J., Barkhurst, A., Duran, R., Nelson, J., Sabbatino, M., Wenzlick, M., Wingo, P., Zaengle, D. and Rose, K. (2021, April 9). Forecasting Offshore Platform Integrity: Applying Machine Learning Algorithms to Quantify Lifespan and Mitigate Risk [Conference presentation]. Machine Learning in Oil & Gas. April 15, 2021. Virtual. https://edx.netl.doe.gov/sites/offshore/forecasting-offshore-platform-integrity-applying-machine-learning-algorithms-to-quantify-lifespan-and-mitigate-risk/

Sealing of Fractures in a Representative CO2 Reservoir Caprock by Migration of Fines

Rod, K.A.; Cantrell, K.J.; Varga, T.; Battu, A.; Brown, C.F. Sealing of Fractures in a Representative CO2 Reservoir Caprock by Migration of Fines. Greenhouse Gases: Science and Technology 2021. 11(3), 483-492. PNNL-SA-160332, https://doi.org/10.1002/ghg.2061

ML Clustering to Identify Natural Gas Pipeline Infrastructure Vulnerabilities

Bauer, J., Justman, D., and Rose. K. Invited presentation. Machine Learning Clustering to Identify Natural Gas Pipeline Infrastructure Vulnerabilities. Department of Homeland Security Science & Technology Directorate 2021 Big Data Series Workshop, March 24, 2021. https://www.osti.gov/biblio/1814179

Public Data from Three US States Provide New Insights into Well Integrity

Lackey, G., Rajaram, H., Bolander, J., Sherwood, O.A., Ryan, J.N., Shih, C.Y., Bromhal, G.S., and Dilmore, R.M., “Public Data from Three US States Provide New Insights into Well Integrity,” Proceedings of the National Academy of Sciences of the United States of America, 118 (14) e2013894118. https://doi.org/10.1073/pnas.2013894118

Evaluation of the Economic Implications of Varied Pressure Drawdown Strategies Generated Using a Real-time, Rapid Predictive, Multi-Fidelity Model for Unconventional Oil and Gas Wells

Bello, K., Vikara, D., Sheriff, A., Viswanathan, H., Carr, T., Sweeney, M., O’Malley, D., Marquis, M., Vactor, R.T., and Cunha, L., “Evaluation of the Economic Implications of Varied Pressure Drawdown Strategies Generated Using a Real-time, Rapid Predictive, Multi-Fidelity Model for Unconventional Oil and Gas Wells,” Gas Science and Engineering, (2023) https://doi.org/10.1016/j.jgsce.2023.204972.

A Quantitative Risk Assessment Approach for Developing Contingency Plans at a Geologic Carbon Storage Site

Mitchell, N.; Lackey, G.; Schwartz, B.; Strazisar, B.; Dilmore, R. A Quantitative Risk Assessment Approach for Developing Contingency Plans at a Geologic Carbon Storage Site. Greenhouse Gases: Science and Technology 2023, 13(3), 320-339. https://doi.org/10.1002/ghg.2219.

Evaluating Probability of Containment Effectiveness at a GCS Site using Integrated Assessment Modeling Approach with Bayesian Decision Network

Wang, Z.; Dilmore, R. M.; Bacon, D. H.; Harbert, W. Evaluating Probability of Containment Effectiveness at a GCS Site using Integrated Assessment Modeling Approach with Bayesian Decision Network, Greenhouse Gases: Science and Technology, 2021, 11(2), 360-376. https://doi.org/10.1002/ghg.2056.

Modeling‐Based Assessment of Deep Seismic Potential Induced by Geologic Carbon Storage

Chang, K.W., and Yoon, H., “Modeling‐Based Assessment of Deep Seismic Potential Induced by Geologic Carbon Storage,” Seismological Research Letters, 49(3), 1447–1454, (2023) https://doi.org/10.1785/0220220365.

Joint Physics-Based and Data-Driven Time-Lapse Seismic Inversion: Mitigating Data Scarcity

Liu, Y., Feng, S., Tsvankin, I., Alumbaugh, D., and Lin, Y., “Joint Physics-Based and Data-Driven Time-Lapse Seismic Inversion: Mitigating Data Scarcity,” Geophysics, (2022) doi.org/10.1190/geo2022-0050.1.

NRAP Recommended Practices for Containment Assurance and Leakage Risk Quantification

Thomas, R. B.; Schwartz, B.; Oldenburg, C.; Bacon, D. H.; Gasperikova, E.; Lackey. G.; Appriou, D.; Harp, D.; Chen, B.; Doughty, C.; Burghardt, J.; Pawar, R. J.; Brown, C. F.; Smith, M. M.; Van Voorhees, R.; Strazisar, B. R.; Dilmore, R. M. NRAP Recommended Practices for Containment Assurance and Leakage Risk Quantification; NRAP-TRS-I-002-2022; DOE.NETL-2022.3344; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Pittsburgh, PA, 2022; p 76. DOI: 10.2172/1906399 https://www.osti.gov/biblio/1906399/

Computational Tools and Workflows for Quantitative Risk Assessment and Decision Support for Geologic Carbon Storage Sites: Progress and Insights from the U.S. DOE’s National Risk Assessment Partnership

Dilmore, R. M.; Appriou, D.; Bacon, D.; Brown, C.; Cihan, A.; Gasperikova, E.; Kroll, K.; Oldenburg, C. M.; Pawar, R. J.; Smith, M. M.; Strazisar, B. R.; Templeton, D.; Thomas, R. B.; Vasylkivska, V. S.; White, J. A. Computational Tools and Workflows for Quantitative Risk Assessment and Decision Support for Geologic Carbon Storage Sites: Progress and Insights from the U.S. DOE’s National Risk Assessment Partnership. 16th International Conference on Greenhouse Gas Control Technologies, GHGT-16, 23-24th October 2022, Lyon, France. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4298480

Extended Abstract to: Integrating Qualitative and Quantitative Risk Assessment Methods for Carbon Storage: A Case Study for the Quest Carbon Capture and Storage Facility

Brown, C. F.; Lackey, G.; Schwartz, B.; Deane, M.; Dilmore, R.; Blanke, H.; O’Brien, S.; Rowe, C. O’Brien, S.; Rowe, C. Extended Abstract to: Integrating Qualitative and Quantitative Risk Assessment Methods for Carbon Storage: A Case Study for the Quest Carbon Capture and Storage Facility. 16th International Conference on Greenhouse Gas Control Technologies, GHGT-16, 23-24th October 2022, Lyon, France. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4297575

High-Quality Fracture Network Mapping Using High Frequency Logging While Drilling (LWD) Data: MSEEL Case Study

Fathi, E., Carr, T.R., Adenan, M.F., Panetta, B., Kumar, A., and Carney, B.J., ”High-Quality Fracture Network Mapping Using High Frequency Logging While Drilling (LWD) Data: MSEEL Case Study,” Machine Learning with Applications, Vol. 10 (2022), https://doi.org/10.1016/j.mlwa.2022.100421.

Reduced Order Modeling for Flow and Transport Problems with Barlow Twins Self-Supervised Learning

Kadeethum, T., Ballarin, F., O’Malley, D., Choi, Y., Bouklas, N., and Yoon, H., “Reduced Order Modeling for Flow and Transport Problems with Barlow Twins Self-Supervised Learning,” Scientific Reports, 12, Article 20654 (2022), https://doi.org/10.1038/s41598-022-24545-3.

EDX++: Migrating EDX to the Cloud, Unlocking Next-Generation Data Infrastructure

Baker, V. Rose, K. Obradovich, J. McFarland, D. Jones, TJ. Mondello, J. Dean, E. Sarle, J. (2023, August 28). EDX++: Migrating EDX to the Cloud, Unlocking Next-Generation Data Infrastructure [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS28_Baker.pdf

Developing a National Structural Complexity Database for U.S. Saline Basins

Amrine, D. Justman, D. Creason, C. Pantaleone, S. Gordon, A. Rose, K. (2023, August 28). Developing a National Structural Complexity Database for U.S. Saline Basins [Poster presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTSp_Amrine.pdf

Managing Carbon Storage Data With a Living Database

Sabbatino, M. Morkner, P. Choisser, A. Leveckis, S. Bauer, J. Rose, K. (2023, August 28). Managing Carbon Storage Data With a Living Database [Poster presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTSp_Sabbatino.pdf

Machine Learning Based Fracture Network Quantification at the IBDP CO2 Sequestration Site

Kumar, A. Harbert, W. Liu, G. Myshakin, E.(2023, August 28). Machine Learning Based Fracture Network Quantification at the IBDP CO2 Sequestration Site [Poster presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTSp_Kumar.pdf 

Class II to Class IV Operations – Insights from Simulation-Based Investigation of a CO2-EOR to Dedicated Storage Scenario

Liu, G. Dilmore, R. Strazisar, B. Lackey, G. (2023, August 28). Class II to Class IV Operations – Insights from Simulation-Based Investigation of a CO2-EOR to Dedicated Storage Scenario [Poster presentation]. FECM/NETL Carbon Management Meeting 2023.  https://netl.doe.gov/sites/default/files/netl-file/23CM_CTSp_Liu.pdf

Application of NRAP Risk Assessment Tools in the Context of Bowtie Risk Management Framework

Brown, C. Lackey, G. Mitchell, N. Baek, S. Schwartz, B. Dean, M. Dilmore, R. Blanke, H. Rowe, C. (2023, August 28). Application of NRAP Risk Assessment Tools in the Context of Bowtie Risk Management Framework [Poster presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTSp_Brown.pdf

Conceptualizing Data Availability and Technical Viability Methods within the Carbon Storage Technical Viability (CS TVA) Approach

Mulhern, J. Mark-Moser, M. Creason, C. Shay, J. Rose, K. (2023, August 28). Conceptualizing Data Availability and Technical Viability Methods within the Carbon Storage Technical Viability (CS TVA) Approach [Poster presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTSp_Mulhern.pdf

Carbon Storage Program Data Curation, Transformation and Reuse

Morkner, P. Bauer, J. Choisser, A. Sabbatino, M. Leveckis, S. Rose, K. (2023, August 28) Carbon Storage Program Data Curation, Transformation and Reuse [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS28_Morkner.pdf

EJ/SJ Dynamic Datasets for CCS Systems and the Energy Transition Web Atlas Tool

Sharma, M. White, C. Cleaveland, C. Romeo, L. Bauer, J. Rose, K. (2023, August 28). EJ/SJ Dynamic Datasets for CCS Systems and the Energy Transition Web Atlas Tool [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS28_Sharma.pdf

Developing a National Structural Complexity Database for U.S. Saline Basins

Justman, D. Creason, C. Pantaleone, S. Gordon, A. Amrine, D. Rose, K. (2023, August 28). Developing a National Structural Complexity Database for U.S. Saline Basins [Conference presentation]. FECM/NETL Carbon Management Meeting 2023.  https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS28_Justman.pdf

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