Justman, D., Creason, C. G., Pantaleone, S., Amrine, D., Rose, K. (2023, October 15-18). Developing a National Structural Complexity Database for U.S. Saline Basins [Conference presentation]. Geological Society of America Annual Meeting. Pittsburgh, PA. https://gsa.confex.com/gsa/2023AM/meetingapp.cgi/Paper/391762
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Bibliographies
Developing a National Structural Complexity Database for U.S. Saline Basins
Carbon Storage Open Data Geospatial Curation and Accessibility
Choisser, A., Morkner, P., Sabbatino, M., Bauer, J., Rose, K. (2023, October 16-18). Carbon Storage Open Data Geospatial Curation and Accessibility [Conference presentation]. Geological Society of America Annual Meeting. Pittsburgh, PA. https://community.geosociety.org/gsa2023/home
RokBase: Digital Rock Visualization and Exploration Web Application
Sharma, M. Paronish, T. Crandall, D. Naberhaus, T. Nakacwa, S. (2023, October 16). RokBase: Digital Rock Visualization and Exploration Web Application [Conference presentation]. GSA Connects Conference 2023. https://gsa.confex.com/gsa/2023AM/meetingapp.cgi/Paper/394714
CO2-Locate: A National Oil & Gas Wellbore Database and Visualization Tool to Support Geological and Environmental Assessment
Sharma, M. Romeo, L. Bauer, J. Amrine, D. Pfander, I. Sabbatino, M. Rose, K. (2023, October 15) CO2-Locate: A National Oil & Gas Wellbore Database and Visualization Tool to Support Geological and Environmental Assessment [Conference presentation]. GSA Connects Conference 2023. https://gsa.confex.com/gsa/2023AM/meetingapp.cgi/Paper/395013
Carbon Storage Technical Viability Approach (CS TVA): Multi-Factor Data Assessment Workflow to Determine Geologic Sequestration Feasibility
Mulhern, J., Mark-Moser, M., Creason, C.G., Shay, J., and Rose, K., “Carbon Storage Technical Viability Approach (CS TVA): Multi-Factor Data Assessment Workflow to Determine Geologic Sequestration Feasibility,” Geological Society of America Annual Meeting, Pittsburgh, PA, October 15–18, 2023.
F.C. Deemer Repository: Chemostratigraphic Characterization of the Baker Run Reserve No. 8 Well in Clearfield County, Pennsylvania, USA
Paronish, T., Cardenas, K., Crandall, D., and Jarvis, K., “F.C. Deemer Repository: Chemostratigraphic Characterization of the Baker Run Reserve No. 8 Well in Clearfield County, Pennsylvania, USA,” Geological Society of America Annual Meeting, Pittsburgh, PA, October 15–18, 2023.
NETL Core Characterization Lively Grove #1 St. Peter Sandstone
Crandall, D., Paronish, T., Workman, S., Gill, M., Jarvis, K., and Brandi, M., “NETL Core Characterization Lively Grove #1 St. Peter Sandstone,” Illinois Storage Corridor All Hands Meeting, Champaign, IL, September 26, 2023.
Understanding Federal Data Curation Requirements and EDX++ Tool to Serve CS Data Curation Needs
Rowan, C. Sinclair, J. (2023, August 31). Understanding Federal Data Curation Requirements and EDX++ Tool to Serve CS Data Curation Needs [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS31_Rowan.pdf
DOE’s Carbon Matchmaker
Sharma, M. Dooley, K. (2023, August 31). DOE’s Carbon Matchmaker [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS31_Sharma.pdf
Carbon Storage Bipartisan Infrastructure Law Communications and Stakeholder Engagements
Wanosky, G. Sinclair, J. (2023, August 31). Carbon Storage Bipartisan Infrastructure Law Communications and Stakeholder Engagements [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS31_Wanosky.pdf
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.
Regulatory Considerations for Geologic Storage of Carbonated Brine Streams. 16th International Conference on Greenhouse Gas Control Technologies
Van Voorhees, R.; Thomas, R. B.; Schwartz, B.; Dilmore, R.; Hamling, J.; Klapperich, R.; Taunton, M. Regulatory Considerations for Geologic Storage of Carbonated Brine Streams. 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=4285028
NETL RIC’s Carbon Storage Research Supporting Field Efforts (FWP-1022403)
Crandall, D. (2021, August 5). NETL RIC’s Carbon Storage Research Supporting Field Efforts (FWP-1022403) [Conference presentation]. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Crandall5.pdf
Modeling the MT and CSEM Response scCO2 Plume at the Kemper CarbonSAFE Site (FWP-1022403)
Hammack, R. (2021, August 5). Modeling the MT and CSEM Response scCO2 Plume at the Kemper CarbonSAFE Site (FWP-1022403) [Conference presentation]. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Hammack5.pdf
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
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/
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
Incorporating Historical Data and Past Analyses for Improved Tensile Property Prediction of 9% Cr Steel
Wenzlick, M., Devanathan, R., Mamun, O., Rose, K., Hawk, J., 2021. Incorporating historical data & past analyses for improved tensile property prediction of 9Cr steel. 2021 TMS Annual Meeting & Exhibition, AI/Data informatics: Design of Structural Materials, Orlando, FL, March 2021. https://www.researchgate.net/publication/349544140_Incorporating_Historical_Data_and_Past_Analyses_for_Improved_Tensile_Property_Prediction_of_9_Cr_Steel
Tools for Data Collection, Curation, and Discovery to Support Carbon Storage Insights
Mark-Moser, M., Rose, K., Baker, V. D. (2020, December 17). Tools for Data Collection, Curation, and Discovery to Support Carbon Storage Insights. [Conference presentation]. Session: IN042 – Utilizing unstructured data in Earth Science Poster Session. https://ui.adsabs.harvard.edu/abs/2020AGUFMIN0140002M/abstract
NRAP-Open-IAM: A New, Open-Source Code for Integrated Assessment of Geologic Carbon Storage Containment Effectiveness and Leakage Risk
Vasylkivska, V., Bacon D., Chen, Bailian, Dilmore R., Harp D., King S., Lackey G., Lindner E., Liu Guoxiang, Mansoor K., Zhang Yingqi. NRAP-Open-IAM: A New, Open-Source Code for Integrated Assessment of Geologic Carbon Storage Containment Effectiveness and Leakage Risk. AGU Annual Fall Meeting (Virtual), 2020 Session: GC110. Advances in Computational Methods for Geologic CO2 Sequestration I eLightning. https://ui.adsabs.harvard.edu/abs/2020AGUFMGC110..10V/abstract
Developing a structured seafloor sediment database from disparate datasets using SmartSearch
Mark-Moser, M., Rose, K., Baker, V. D. 2020. Developing a structured seafloor sediment database from disparate datasets using SmartSearch. AGU Annual Fall Meeting (Virtual), 2020. Session: IN042 – Utilizing unstructured data in earth science https://www.osti.gov/servlets/purl/1776797