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
disCO2ver
Unlocking data-driven capabilities for the entire CTS community
Bibliographies
NETL RIC’s Carbon Storage Research Supporting Field Efforts (FWP-1022403)
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
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.
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
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
Possible Controls on Porosity Preservation in the Andaman Forearc Gas Hydrate System
Johnson, J., Rose, K., Torres, M. (2020, Jan). Possible controls on porosity preservation in the Andaman forearc gas hydrate system: OSR, AOM, and/or marine silicate weathering [Conference presentation]. Geologic Society of America Meeting 2020, Session: T99. Records of Early Diagenesis in Modern and Ancient Sediments. https://community.geosociety.org/gsa2020/program/technical
Back to the Future: Rescue, Curation, and Transformation of a Corpus of Carbon Storage Data
Sabbatino, M., Baker, V., Bauer, J., Creason, C., Romeo, L., Rose, K., Rowan, C., Zoch, G., submitted, Back to the Future: Rescue, Curation, and Transformation of a Corpus of Carbon Storage Data, Annual Meeting 2019, Session: AGU Dirty Stories of Data Rescue. https://www.osti.gov/servlets/purl/1778129
Developing a Virtual Subsurface Data Framework: Transforming DOE’s EDX data lake using ML/NLP
Rose, R. Rowan, C., Sabbatino, M., Baker, V., Bauer, J., Creason, C.G., Jones, T.J., Justman, D., Romeo, L., Suhag, A., Yeates, D., and Walker, S., submitted, Developing a Virtual Subsurface Data Framework: Transforming DOE’s EDX data lake using ML/NLP, Annual Meeting 2019, Session: IN020 – Data Integration: Enabling the Acceleration of Science Through Connectivity, Collaboration, and Convergent Science. https://agu.confex.com/agu/fm19/meetingapp.cgi/Paper/596761
Moving data “rocks” out of hard places: adapting and innovating data science tools to improve geoscience analytics
Yeates, D., Walker, S., Fillingham, J., Sabbatino, M., Suhag, A., Rose, K., Mark-Moser, M., Creason, C.G., Baker, V., submitted, Moving data “rocks” out of hard places: adapting and innovating data science tools to improve geoscience analytics, AGU Annual Meeting 2019, Session IN005 – AI for Model and Data Integration in the Geosciences. https://ui.adsabs.harvard.edu/abs/2019AGUFMIN32B..09Y/abstract
Subsurface Trend Analysis
Rose, K., Mark-Moser, M., Suhag, A. Subsurface Trend Analysis: A methodical framework for artificial intelligence subsurface property prediction. Machine Learning for Unconventional Resources, Nov. 18th 2019, University of Houston, Texas. https://www.osti.gov/servlets/purl/1778138
Putting Data to Work: Transforming Disparate Open-Source Data for Engineered-Natural Systems and Models
Creason, C.G., Romeo, L., Bauer, J., Rose, K., Rowan, C., and Sabbatino, M., 2019, Putting Data to Work: Transforming Disparate Open-Source Data for Engineered-Natural Systems and Models, AGU Annual Meeting 2019, Session: IN020 – Data Integration: Enabling the Acceleration of Science Through Connectivity, Collaboration, and Convergent Science. https://www.osti.gov/biblio/1778210