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
Discover
Unlocking data-driven capabilities for the entire transport and storage community
Home » Bibliographies
Bibliographies
A systematic, science-driven approach for predicting subsurface properties
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
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
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
Estimating Carbon Storage Resources in Offshore Geologic Environments
Cameron, E.; Thomas, R.; Bauer, J.; Bean, A.; DiGiulio, J.; Disenhof, C.; Galer, S.; Jones, K.; Mark-Moser, M.; Miller, R.; Romeo, L.; Rose, K. Estimating Carbon Storage Resources in Offshore Geologic Environments; NETL-TRS-14-2018; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Albany, OR, 2018; p 32. DOI: 10.18141/1464460 https://edx.netl.doe.gov/dataset/estimating-carbon-storage-resources-in-offshore-geologic-environments
Signatures in the Subsurface – Big & Small Data Approaches for the Spatio-Temporal Analysis of Geologic Properties & Uncertainty Reduction
Rose, K., “Signatures in the Subsurface – Big & Small Data Approaches for the Spatio-Temporal Analysis of Geologic Properties & Uncertainty Reduction,” 2016, http://hdl.handle.net/1957/59459.
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
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.