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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

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

Class II to Class IV Operations – Insights from Simulation-Based Investigation of a CO2-EOR to Dedicated Storage Scenario

Liu, G. Dilmore, R. Strazisar, B. Lackey, G. (2023, August 28). Class II to Class IV Operations – Insights from Simulation-Based Investigation of a CO2-EOR to Dedicated Storage Scenario [Poster presentation]. FECM/NETL Carbon Management Meeting 2023.  https://netl.doe.gov/sites/default/files/netl-file/23CM_CTSp_Liu.pdf

Application of NRAP Risk Assessment Tools in the Context of Bowtie Risk Management Framework

Brown, C. Lackey, G. Mitchell, N. Baek, S. Schwartz, B. Dean, M. Dilmore, R. Blanke, H. Rowe, C. (2023, August 28). Application of NRAP Risk Assessment Tools in the Context of Bowtie Risk Management Framework [Poster presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTSp_Brown.pdf

Conceptualizing Data Availability and Technical Viability Methods within the Carbon Storage Technical Viability (CS TVA) Approach

Mulhern, J. Mark-Moser, M. Creason, C. Shay, J. Rose, K. (2023, August 28). Conceptualizing Data Availability and Technical Viability Methods within the Carbon Storage Technical Viability (CS TVA) Approach [Poster presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTSp_Mulhern.pdf

Carbon Storage Program Data Curation, Transformation and Reuse

Morkner, P. Bauer, J. Choisser, A. Sabbatino, M. Leveckis, S. Rose, K. (2023, August 28) Carbon Storage Program Data Curation, Transformation and Reuse [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS28_Morkner.pdf

EJ/SJ Dynamic Datasets for CCS Systems and the Energy Transition Web Atlas Tool

Sharma, M. White, C. Cleaveland, C. Romeo, L. Bauer, J. Rose, K. (2023, August 28). EJ/SJ Dynamic Datasets for CCS Systems and the Energy Transition Web Atlas Tool [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS28_Sharma.pdf

Developing a National Structural Complexity Database for U.S. Saline Basins

Justman, D. Creason, C. Pantaleone, S. Gordon, A. Amrine, D. Rose, K. (2023, August 28). Developing a National Structural Complexity Database for U.S. Saline Basins [Conference presentation]. FECM/NETL Carbon Management Meeting 2023.  https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS28_Justman.pdf

Carbon Storage Technical Viability Approach

Mark-Moser, M. Creason, C. Mulhern, J. Shay, J. Lara, A. Rose, K. (2023, August 28). Carbon Storage Technical Viability Approach [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS28_Mark-Moser.pdf

EDX Utilization of Cloud Open Data Programs to Enhance Reuse of Large CS Datasets

Rowan, C. Rose, K. (2023, August 28). EDX Utilization of Cloud Open Data Programs to Enhance Reuse of Large CS Datasets. FECM/NETL Carbon Management Meeting 2023 [Conference presentation].  https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS28_Rowan.pdf

CS BIL Communications and Stakeholder Outreach

Wanosky, G., and Sinclair, J., “CS BIL Communications and Stakeholder Outreach,” 2023 Carbon Management Research Project Review Meeting, Pittsburg, PA, August 28–September 1, 2023.

Deploying a National Well Database to Support CS Reuse and Risk

 Romeo, L., Bauer, J., Amrine, D., Pfander, I., Mulhern, J., Sabbatino, M., and Rose, K., “Deploying a National Well Database to Support CS Reuse and Risk”. 2023 Carbon Management Research Project Review Meeting, Pittsburg, PA, August 28–September 1, 2023.

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