Duran, R., Dyer, A., Mark-Moser, M., Bauer, J., Rose, K., Zaengle. D., Wingo, P. 2020. A Geospatial Analytical Framework to Identify Seafloor Geohazards in the Northern Gulf of Mexico. AGU Annual Meeting 2020, Session: NH010 – Geohazards in Marine and Lacustrine Environments. https://ui.adsabs.harvard.edu/abs/2020AGUFMNH004..08D/abstract
disCO2ver
Unlocking data-driven capabilities for the entire CTS community
Bibliographies
A Geospatial Analytical Framework to Identify Seafloor Geohazards in the Northern Gulf of Mexico
Optimizing Prediction of Reservoir Properties with Artificial Intelligence, Big Data, and the Subsurface Trend Analysis Method
Mark-Moser, M., Suhag, A., Rose, K., Wingo, P. (2020, November 9). Optimizing prediction of reservoir properties with artificial intelligence, big data, and the Subsurface Trend Analysis method [Conference presentation]. Machine Learning for Oil and Gas 2020, Nov. 9-11, Virtual. https://edx.netl.doe.gov/sites/offshore/optimizing-prediction-of-reservoir-properties-with-artificial-intelligence-big-data-and-the-subsurface-trend-analysis-method/
Advanced Geospatial Analytics and Machine Learning for Offshore and Onshore Oil & Natural Gas Infrastructure
Justman D., Romeo, L., Barkhurst, A., Bauer, J., Duran, R., Dyer, A., Nelson, J., Sabbatino, M., Wingo, P., Wenzlick, M., Zaengle, D., Rose, K. (2020, October 6-7). Advanced geospatial analytics and machine learning for offshore and onshore oil & natural gas infrastructure. [Virtual conference presentation]. GIS Week 2020. https://www.osti.gov/servlets/purl/1767074
Enhancing Knowledge Discovery of Unstructured Data to Support Context in Subsurface-Modeling Predictions
Hoover, B., Mark-Moser, M., Wingo, P., Suhag, A., Rose, K. 2021. Enhancing knowledge discovery of unstructured data to support context in subsurface-modeling predictions. ACE/SEG21, Denver, Colorado, Sept. 26th-Oct. 1st. https://www.osti.gov/servlets/purl/1843422
Using AI/ML to Curate Thousands of Carbon Storage Data Assets via EDX
Morkner, P., Rowan, C., Rose, K., Bauer, J., Sabbatino, M., Barhurst, A. Using AI/ML to Curate Thousands of Carbon Storage Data Assets via EDX. NETL Carbon Storage Review Meeting. September 10, 2020. Virtual. https://netl.doe.gov/sites/default/files/netl-file/20CSVPR_Morkner.pdf
Assessing Offshore CO2 Saline Storage Potential with the NETL Calculator
Romeo, L., Rose, K., Thomas, R., Mark-Moser, M., Barkhurst, A., Wingo, P., Bean, A. 2020. Assessing Offshore CO2 Saline Storage Potential with the NETL Calculator. Carbon Storage Review Meeting. September 11, 2020. Virtual. https://netl.doe.gov/sites/default/files/netl-file/20CSVPR_Romeo_11.pdf
Exploring Beneath the Basemap
Bauer, J., Justman, D., Mark-Moser, M., Romeo, L., Creason, C.G., and Rose, K., “Exploring Beneath the Basemap,” GIS for Science: Applying Mapping and Spatial Analytics, Vol. 2 (2020), pp. 51–67.
Building an Analytical Framework to Measure Offshore Infrastructure Integrity, Identify Risk, and Strategize Future Use for Oil and Gas
Dyer, A., Romeo, L., Wenzlick, M., Bauer, J., Nelson, J., Duran, R., Zaengle, D., Wingo, P., and Sabbatino, M. 2020. Building an Analytical Framework to Measure Offshore Infrastructure Integrity, Identify Risk, and Strategize Future Use for Oil and Gas. Esri User Conference, San Diego, CA, July 13-15, 2020. https://www.osti.gov/servlets/purl/1604638
Harnessing the Power of DOE Data Computing for End-user Analytics, SMART Webinar
Rose, K., Barkhurst, A., Mark-Moser, M., Romeo, L., and Wingo, P., 2020, Harnessing the Power of DOE Data Computing for End-user Analytics, SMART Webinar 6/25/2020, https://www.youtube.com/watch?v=G5oUWSb-kHc&feature=youtu.be
Building Regional Baselines and a Suite of Spatial Tools to Better Prepare for Oil Spills
Romeo, L., Dyer, A., Nelson, J., Bauer, J., Rose, K., Dao, A., Wingo, P., Creason, C.G., and Sabbatino, M. Building Regional Baselines and a Suite of Spatial Tools to Better Prepare for Oil Spills, AGU Ocean Sciences Meeting 2020, Poster Presentation. https://www.osti.gov/biblio/1787016
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
Machine Learning Application for CCUS Carbon Storage: Fracture Analysis and Mapping in The Illinois Basin
Liu, G., Kumar, A., Harbert, W., Siriwardane, H., Myshakin, E., Crandall, D., Cunha, L., (2024, June 23). Machine Learning Application for CCUS Carbon Storage: Fracture Analysis and Mapping in The Illinois Basin [Conference presentation], ARMA 24–1183, 58th U.S. Rock Mechanics/Geomechanics Symposium, Golden, Colorado. https://www.osti.gov/biblio/2228745
Supporting Safe CO2 Transport-Route Planning: A Multifaceted Geospatial Database Enhancing Carbon Models
Schooley, C., Houghton, B., Romeo, L., Gao, M., Leveckis, S., Justman, D., Chong, L.,Sharma, M., Bauer, J., and Rose, K., “Supporting Safe CO2 Transport-Route Planning: A Multifaceted Geospatial Database Enhancing Carbon Models,” SAMI Technical Talk, San Diego, CA, June 20, 2024.
Advanced Offshore Hazard Forecasting to Enable Resilient Offshore Operations
Mark-Moser, M. K., Romeo, L., Duran, R., Bauer, J., Rose, K., (2024, May 6). Advanced Offshore Hazard Forecasting to Enable Resilient Offshore Operations. [Conference presentation] Offshore Technology Conference 2024. Houston, TX. https://www.osti.gov/biblio/2352616
EDX disCO2ver, Fostering Public-Private Partnerships for Accelerated Advancements in AI for Energy
Rose, K., 2024, “EDX disCO2ver, Fostering Public-Private Partnerships for Accelerated Advancements in AI for Energy”, AI in Oil & Gas Conference, April 9-10, 2024. Invited.
Web-Based GIS Data: Observation of Differences in Performance and Management
Pramuk, J., McFarland, D., Chittum, J., Bauer, J., and Rose, K., “Web-Based GIS Data: Observation of Differences in Performance and Management,” Esri Developer Summit, Palm Springs, CA, March 12–15, 2024.
Carbon Storage Technical Viability Approach and National Data Assessment
Mark-Moser, M., Creason, C.G., Mulhern, J., Shay, J., Lara, A., and Rose, K., “Carbon Storage Technical Viability Approach and National Data Assessment,” presented at the CCUS 2024 SPE AAPG SEG, Houston, TX, March 11–13, 2024.
Developing a National Oil & Gas Wellbore Database and Visualization Tool to Support Locating and Characterizing Undocumented Wells
Bauer, J., Romeo, L., Sharma, M., Amrine, D., Pfander, I., Sabbatino, M., and Rose, K., “Developing a National Oil & Gas Wellbore Database and Visualization Tool to Support Locating and Characterizing Undocumented Wells,” American Geophysical Union (AGU) Fall Meeting 2023, San Francisco, CA, December 11–15, 2023.
Multi-Factor Assessment for Decarbonization via Technically Viable Carbon Storage
Mark-Moser, M., Creason, C.G., Mulhern, J.S., Shay, J., and Rose, K., “Multi-Factor Assessment for Decarbonization via Technically Viable Carbon Storage,” American Geophysical Union (AGU) Fall Meeting 2023, San Francisco, CA, December 11–15, 2023.
The DisCO2ver Platform: Curating Data and Tools for Geologic Carbon Sequestration and Deep Subsurface Systems Research
Morkner, P., Rose, K., Rowan, C., Jones, TJ., McFarland, D., Maurice, A., Baker, V., and Bauer, J., “The DisCO2ver Platform: Curating Data and Tools for Geologic Carbon Sequestration and Deep Subsurface Systems Research,” American Geophysical Union (AGU) Fall Meeting 2023, San Francisco, CA, December 11–15, 2023.
An Accessible and Interoperable CO2 Transport Routing Geodatabase for Scalable Computing & Decision Support
Schooley, C., Romeo, L., Pfander, I., Justman, D., Sharma, M., Bauer, J., and Rose, K., “An Accessible and Interoperable CO2 Transport Routing Geodatabase for Scalable Computing & Decision Support,” American Geophysical Union (AGU) Fall Meeting 2023, San Francisco, CA, December 11–15, 2023.