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.
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Bibliographies
Multi-Factor Assessment for Decarbonization via Technically Viable Carbon Storage
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.
An Environmental, Energy, Economic, and Social Justice Database for Carbon Capture and Storage Applications
Sharma, M., White, C., Cleaveland, C., Romeo, L., Rose, K., and Bauer, J., “An Environmental, Energy, Economic, and Social Justice Database for Carbon Capture and Storage Applications,” American Geophysical Union (AGU) Fall Meeting 2023, San Francisco, CA, December 11–15, 2023.
Developing a Data Integration and Curation Method from Siloed Resources with Multi-Discipline Applicability
Romeo, L., Bauer, J., Pfander, I., Sabbatino, M., Wenzlick, M., and Rose, K., “Developing a Data Integration and Curation Method from Siloed Resources with Multi-Discipline Applicability,” DOE Data Days, October 24–26, 2023.
How to Flatten the Earth: Reviewing DOE’s Use of Coordinate Systems to Inform Agency-Wide Guidance
Bauer, J., Linard, J., Cuneo, M., and Zvolanek, E., “How to Flatten the Earth: Reviewing DOE’s Use of Coordinate Systems to Inform Agency-Wide Guidance,” DOE Data Days, October 24–26, 2023.
Energy Data eXchange: NETL’s Digital Library and Virtual Laboratory Supporting the Fossil Energy and Carbon Management Research Community
Kuhn, K., Rose, K., Rowan, C., Bauer, J., Jones, T., Baker, V., McFarland, D., Obradovich, J., Maurice, A., Mondello, J., Williams, T., and Dehlin, M., “Energy Data eXchange: NETL’s Digital Library and Virtual Laboratory Supporting the Fossil Energy and Carbon Management Research Community,” DOE Data Days, October 24–26, 2023, https://data-science.llnl.gov/d3.
EDX Spatial: Leveraging Cloud and Hybrid Data Management Resources for Spatial Data
Morkner, P., Bauer, J., Pramuk, J., Sabbatino, M., Kuhn, K., Choisser, A., Justman, D., Schooley, C., and Rose, K., “EDX Spatial: Leveraging Cloud and Hybrid Data Management Resources for Spatial Data,” DOE Data Days, October 24–26, 2023.
Dynamic risk assessment for geologic CO2 sequestration
Chen, B.; Harp, D. R.; Zhang, Y.; Oldenburg, C. M.; Pawar, R. J. (in Press, Corrected Proof). Dynamic risk assessment for geologic CO2 sequestration. Gondwana Research 2022. https://doi.org/10.1016/j.gr.2022.08.002.
Integrating Risk Assessment Methods for Carbon Storage: A Case Study for the Quest Carbon Capture and Storage Facility
Brown, C. F., G. Lackey, N. Mitchell, S. Baek, B. Schwartz, M. Dean, R. Dilmore, H. Blanke, S. O’Brien, and C. Rowe. 2023. “Integrating Risk Assessment Methods for Carbon Storage: A Case Study for the Quest Carbon Capture and Storage Facility.” International Journal of Greenhouse Gas Control 129: 103972. https://doi.org/10.1016/j.ijggc.2023.103972.
NRAP-Open-IAM: Generic Aquifer Component Development and Testing
Bacon, D. H. NRAP-Open-IAM: Generic Aquifer Component Development and Testing. PNNL-32590, 2022, Pacific Northwest National Laboratory, Richland, WA. https://doi.org/10.2172/1845855.
Machine Learning Enhanced Seismic Monitoring at 100 km and 10 m Scales
Chai, C., Maceira, M., and EGS Collab Team, “Machine Learning Enhanced Seismic Monitoring at 100 km and 10 m Scales,” in Proceedings, 47th Workshop on Geothermal Reservoir Engineering, edited, Stanford University, Stanford, California, 47, 635–645, (2022) https://www.osti.gov/biblio/1845768.
Sensitivity of geophysical techniques for monitoring secondary CO2 storage plumes
Gasperikova, E.; Appriou, D.; Bonneville, A.; Feng, Z.; Huang, L.; Gao, K.; Yang, X.; Daley, T. Sensitivity of geophysical techniques for monitoring secondary CO2 storage plumes. International Journal of Greenhouse Gas Control 2022, 114, Article 103585. https://doi.org/10.1016/j.ijggc.2022.103585.
Scaling Behavior of Thermally Driven Fractures in Deep Low-Permeability Formations: A Plane Strain Model with 1-D Heat Conduction
Chen, B.; Zhou, Q. Scaling Behavior of Thermally Driven Fractures in Deep Low-Permeability Formations: A Plane Strain Model with 1-D Heat Conduction. Journal of Geophysical Research – Solid Earth 2022, Research Article. https://doi.org/10.1029/2021JB022964.
Distilling Data to Drive Carbon Storage Insights
Morkner, P.; Bauer, J.; Creason, C.; Sabbatino, M.; Wingo, P.; Greenburg, R.; Walker, S.; Yeates, D.; Rose, K. Distilling Data to Drive Carbon Storage Insights. Computers & Geosciences 2022, 158, Article 104945. https://doi.org/10.1016/j.cageo.2021.104945.
Deep Learning Inversion of Gravity Data for Detection of CO2 Plumes in Overlying Aquifers
Yang, X.; Chen, X.; Smith, M.M. Deep Learning Inversion of Gravity Data for Detection of CO2 Plumes in Overlying Aquifers. Journal of Applied Geophysics 2022, 196(104507). https://doi.org/10.1016/j.jappgeo.2021.104507.
A Review of Well Integrity Based on Field Experience at Carbon Utilization and Storage Sites
Iyer, J.; Lackey, G.; Edvardsen, L.; Bean, A.; Carroll, S.A.; Huerta, N.; Smith, M.M.; Torsaeter, M.; Dilmore, R.M.; Cerasi, P. A Review of Well Integrity Based on Field Experience at Carbon Utilization and Storage Sites. International Journal of Greenhouse Gas Control 2022, 113(103533). https://doi.org/10.1016/j.ijggc.2021.103533
A Review of Well Integrity Based on Field Experience at Carbon Utilization and Storage Sites
Iyer, J.; Lackey, G.; Edvardsen, L.; Bean, A.; Carroll, S.A.; Huerta, N.; Smith, M.M.; Torsaeter, M.; Dilmore, R.M.; Cerasi, P. A Review of Well Integrity Based on Field Experience at Carbon Utilization and Storage Sites. International Journal of Greenhouse Gas Control 2022, 113(103533). https://doi.org/10.1016/j.ijggc.2021.103533
Impact of time-dependent deformation on geomechanical risk for geologic carbon storage
Bao T.; Burghardt, J. A.; Gupta, V.; White, M. D. Impact of time-dependent deformation on geomechanical risk for geologic carbon storage. International Journal of Rock Mechanics and Mining Sciences 2021, 148, 104940. PNNL-SA-161528. https://doi.org/10.1016/j.ijrmms.2021.104940.
NETL Well Integrity Workshop: Identifying Well Integrity Research Needs for Subsurface Energy Infrastructure
Lackey, G.; Dilmore, R. NETL Well Integrity Workshop: Identifying Well Integrity Research Needs for Subsurface Energy Infrastructure; DOE/NETL-2021/2660; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Pittsburgh, PA, 2021; p 100. DOI: 10.2172/1828877 https://www.osti.gov/biblio/1828877
Probabilistic Machine Learning for Integrated Social-Natural-Physical Assessment
Ghanem, R., Zhang, R., Rose, K., invited talk, Probabilistic Machine Learning for Integrated Social-Natural-Physical Assessment, AGU Annual Meeting 2020, Session: H027 – Artificial Intelligence and Machine Learning for Multiscale Model-Experimental Integration https://agu.confex.com/agu/fm20/prelim.cgi/Session/103051
Deep Learning to Locate Seafloor Landslides in High Resolution Bathymetry
Dyer, A., Zaengle, D., Mark-Moser, M., Duran, R., Suhag, A., Rose, K., Bauer, J. Deep Learning to Locate Seafloor Landslides in High Resolution Bathymetry. AGU Annual Fall Meeting (Virtual), 2020. Session: NH007 – Data Science and Machine Learning for Natural Hazard Sciences II Posters. https://www.osti.gov/servlets/purl/1779617
A Geospatial Analytical Framework to Identify Seafloor Geohazards in the Northern Gulf of Mexico
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
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
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