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
disCO2ver
Unlocking data-driven capabilities for the entire CTS community
Bibliographies
A Review of Well Integrity Based on Field Experience at Carbon Utilization and Storage Sites
Development of Machine Learning Models for Full Field Reservoir Characterization
Wu, X., Shih, C., Mark-Moser, M., and Wingo, P., 2021. Development of machine learning models for full field Reservoir Characterization. AGU Fall Meeting 2021, Dec. 13-17, New Orleans, LA/Virtual. Session H34D – Application of Multimodal Physics-Informed Machine Learning/Deep Learning in Subsurface Flow and Transport Modeling. https://www.osti.gov/servlets/purl/1846178
Science-based Artificial Intelligence and Machine Learning (AI/ML) Institute (SAMI) – Accelerating Cross-Disciplinary AI/ML for Applied Geoscience, Energy, and Environmental Challenges
Shih, C., Thornton, J., Rose, K., Syamlal, M., Bromhal, G., Guenther, C., Pfautz, J., Van Essendelft, D., and Bauer, J., 2021, Science-based Artificial Intelligence and Machine Learning (AI/ML) Institute (SAMI) – accelerating cross-disciplinary AI/ML for applied geoscience, energy, and environmental challenges. AGU Fall Meeting 2021, Dec. 13-17, New Orleans, LA/Virtual. Session: IN12A – Growing Opportunities for Multiparty Collaborations in Artificial Intelligence and Machine Learning for Science Research. https://ui.adsabs.harvard.edu/abs/2021AGUFMIN12A..05S/abstract
Improving Prediction of Subsurface Properties Using a Geoscience Informed, Multi-Technique, Artificial Intelligence Approach
Rose, K., Mark-Moser, M., Suhag, A., and Bauer, J. 2021. Improving prediction of subsurface properties using a geoscience informed, multi-technique, artificial intelligence approach (Invited). AGU Fall Meeting 2021, Dec. 13-17, New Orleans, LA/Virtual. Session H33C – Application of Multimodal Physics-Informed Machine Learning/Deep Learning in Subsurface Flow and Transport Modeling. https://ui.adsabs.harvard.edu/abs/2021AGUFM.H33C..01R/abstract
Leveraging Data Ecosystems to Support Earth Science Research for Decarbonization
Morkner, P., Mark-Moser, M., Justman, D., Rowan, C., Bauer, J., and Rose, K., 2021. Leveraging Data Ecosystems to Support Earth Science Research For Decarbonization. AGU Fall Meeting 2021, Dec. 13-17, New Orleans, LA/Virtual. Session U21A-07 – How Earth Science Research Can Help Accelerate the Transition to a Decarbonized Economy. https://ui.adsabs.harvard.edu/abs/2021AGUFM.U21A..07M/abstract
Exploring Subsurface Data Availability on the Energy Data eXchange (EDX)
Morkner, P., Bean, A., Bauer, J., Barkhurst, A., and Rose, K.. 2021. Exploring subsurface data availability on the Energy Data eXchange. AGU Fall Meeting 2021, Dec. 13-17, New Orleans, LA/Virtual. Session: SY039 – Subsurface Storage of Natural Gas, CO2, and Hydrogen: Key Learnings and Future Opportunities. https://www.osti.gov/servlets/purl/1846774
AI/ML Integration for Accelerated Analysis and Forecast of Offshore Hazards
Mark-Moser, M., Wingo, P., Duran, R., Dyer, A., Zaengle, D., Suhag, A., Hoover, B., Pantaleone, S., Shay, J., Bauer, J., and Rose, K. 2021. AI/ML integration for accelerated analysis and forecast of offshore hazards. AGU Fall Meeting 2021, Dec. 13-17, New Orleans, LA/Virtual. Session: EP027 – Proven AI/ML applications in the Earth Sciences. https://www.osti.gov/servlets/purl/1846789
On the Predictability of Loop Current Eddy Shedding Events and Unexpected Links to the Brazil and Guiana Currents
Duran, R., Liang, X.S., Allende-Arandia, M.E., Appendini, C.M., Mark-Moser, M., Rose, K., Bauer, J. 2021. On the predictability of Loop Current Eddy Shedding events and unexpected links to the Brazil and Guiana Currents. AGU Fall Meeting 2021, Dec. 13-17, New Orleans, LA/Virtual. Session: OS45D – Ocean Dynamics of the Gulf of Mexico III Poster. https://www.osti.gov/servlets/purl/1846777
Evaluating the Effects of a Low-Carbon Energy Transition on Existing U.S. Fossil Energy Communities
Bauer, J., Rose, K., Romeo, L., Justman, D., Hoover, B., and B. White. 2021. Evaluating the effects of a low-carbon energy transition on existing U.S. fossil energy communities. AGU Fall Meeting 2021, Dec. 13-17, New Orleans, LA/Virtual. Session GC25G: Environmental Justice/Equity and Global Change: Methodologies, Frameworks, and Results II Poster. https://ui.adsabs.harvard.edu/abs/2021AGUFMGC25G0722B/abstract
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.
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.
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.
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.
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
Aseismic deformations perturb the stress state and trigger induced seismicity during injection experiments
Duboeuf, L.; De Barros, L.; Kakurina, M.; Guglielmi, Y.; Cappa, F.; Valley, B. Aseismic deformations perturb the stress state and trigger induced seismicity during injection experiments. Geophysical Journal International 2021, 224(2), 1464-1475. doi: 10.1093/gji/ggaa515. https://academic.oup.com/gji/article-abstract/224/2/1464/5974524?redirectedFrom=fulltext
A knowledge-data framework and geospatial fuzzy logic-based approach to model and predict structural complexity
Justman, D., Creason, C.G., Rose, K., & Bauer, J., 2020. A knowledge-data framework and geospatial fuzzy logic-based approach to model and predict structural complexity. Journal of Structural Geology, 104153. https://doi.org/10.1016/j.jsg.2020.104153
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.
A systematic, science-driven approach for predicting subsurface properties
Rose, K., Bauer, J.R., and Mark-Moser, M., 2020, A systematic, science-driven approach for predicting subsurface properties. Interpretation, 8:1, 167-181 https://doi.org/10.1190/INT-2019-0019.1
Cumulative spatial impact layers: A novel multivariate spatio‐temporal analytical summarization tool
Romeo, L., Nelson, J., Wingo, P., Bauer, J., Justman, D., Rose, K. 2019. Cumulative spatial impact layers: A novel multivariate spatio‐temporal analytical summarization tool. Transactions in GIS.00:1–29. https://doi.org/10.1111/tgis.12558
Smart CO2 Transport-Route Planning Tool
Rose, K., Romeo, L, Leveckis, S., Gao, M., Houghton, B., Zaengle, D., Schooley, C., Justman, D., and Bauer, J., 2024, Smart CO2 Transport-Route Planning Tool, 15th International Pipeline Conference (IPC 2024), September 2024
The Integration and Mapping of an Open-Source National Well Resource to Inform Geologic Carbon Storage Site Selection and Risk Prevention: The CO2-Locate Database
Tetteh, D.A. Romeo, L. Pfander, I., Dyer, A.S., Sabbatino, M., Sharma, M., Cleaveland, C., McElroy, P., Rose, K., and J. Bauer. “The Integration and Mapping of an Open-Source National Well Resource to Inform Geologic Carbon Storage Site Selection and Risk Prevention: The CO2-Locate Database”. Geologic Society of America Connects, Sept. 2024. Anaheim, CA, 2024.
Spatial Seal Database for Prospective Storage Resources in the USA
Pantaleone, S., Martin, A., Marcelli, O., Morkner, P., and Rose, K., “Spatial Seal Database for Prospective Storage Resources in the USA,” FECM/NETL Carbon Management Research Project Review Meeting, Pittsburgh, PA, August 5–9, 2024.
Smart CO2 Transport-Route Planning Tool: Providing Data and Insights for Accelerating Carbon Transport & Storage Deployment
Romeo, L., Leveckis, S., Gao, M., Houghton, B., Zaengle, D., Schooley, C., Justman, D., Bauer, J. and K. Rose. Smart CO2 Transport-Route Planning Tool: Providing Data and Insights for Accelerating Carbon Transport & Storage Deployment. 2024 FECM / NETL Carbon Management Research Project Review Meeting. Pittsburgh, PA. August 5–9, 2024.
Paving the Way for Stakeholder use of Carbon Storage & Transport Digital Resources
Martin, A., Cleaveland, C., Justman, D., and Morkner, P., “Paving the Way for Stakeholder use of Carbon Storage & Transport Digital Resources,” FECM/NETL Carbon Management Research Project Review Meeting, Pittsburgh PA, August 5–9, 2024. https://netl.doe.gov/sites/default/files/netl-file/24CM/24CM_CTS1_5_Martin.pdf
Basin-Scale Structural Features Database: Spatial Datasets to Support Carbon Storage Resource Assessments
Justman, D., Pantaleone, S., Alexander, J., and Bauer, J., “Basin-Scale Structural Features Database: Spatial Datasets to Support Carbon Storage Resource Assessments,” FECM/NETL Carbon Management Research Project Review Meeting, Pittsburgh, PA, August 5–9, 2024. https://netl.doe.gov/sites/default/files/netl-file/24CM/24CM_CTS3_5_Justman.pdf
Carbon Storage Technical Viability Approach (CS TVA): An Integrated Approach for Feasibility and Data Resource Assessment
Cordero Rodriguez, N., Mulhern J., Creason C.G., Mark-Moser, M., Lara A., Shay J., and Rose, K., “Carbon Storage Technical Viability Approach (CS TVA): An Integrated Approach for Feasibility and Data Resource Assessment,” FECM/NETL Carbon Management Research Project Review Meeting, Pittsburgh, PA, August 5–9, 2024.
Carbon Matchmaker: Connecting CCUS Activities and Stakeholders
Bauer, J., Sharma, M., Rose, K., Dooley, K. Carbon Matchmaker: Connecting CCUS Activities and Stakeholders. FECM/NETL Carbon Management Meeting. Pittsburgh, PA. August 5-9, 2024
Development of the Class VI Mapping Inquiry Tool and Class VI Data Tool Geodatabase
Schooley, C., Morkner, P., Pantaleone, S., Shay, J., Bauer, J., and Strazisar, B., “Development of the Class VI Mapping Inquiry Tool and Class VI Data Tool Geodatabase,” poster presentation for the CCUS 2024 SPE AAPG SEG, Houston, TX, March 11–13, 2024.
International Offshore Geologic Carbon Storage Data Collection, Web Application, Inventory, and Meta-Analysis
Mulhern, J.S., Mark-Moser, M., and Rose, K., “International Offshore Geologic Carbon Storage Data Collection, Web Application, Inventory, and Meta-Analysis,” FECM/NETL Carbon Management Research Project Review Meeting, Pittsburgh, PA, August 5–9, 2024.