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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.

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.

Enhancing Knowledge Discovery from Unstructured Data Using a Deep Learning Approach to Support Subsurface Modeling Predictions

Hoover B, Zaengle D, Mark-Moser M, Wingo P, Suhag A and Rose K. (2023) Enhancing knowledge discovery from unstructured data using a deep learning approach to support subsurface modeling predictions. Front. Big Data 6:1227189. doi: https://doi.org/10.3389/fdata.2023.1227189

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.

A Project Lifetime Approach to the Management of Induced Seismicity Risk at Geologic Carbon Storage Sites

Dennise C. Templeton, Martin Schoenball, Corinne E. Layland‐Bachmann, William Foxall, Yves Guglielmi, Kayla A. Kroll, Jeffrey A. Burghardt, Robert Dilmore, Joshua A. White; A Project Lifetime Approach to the Management of Induced Seismicity Risk at Geologic Carbon Storage Sites. Seismological Research Letters 2022;; 94 (1): 113–122. https://doi.org/10.1785/0220210284

Computed Tomography Scanning and Geophysical Measurements of Appalachian Basin Core from the Jones and Laughlin #1 Well, Beaver County, PA

Sharma, M., Paronish, T., Mitchell, N., Crandall, D., Zerbe, S., Pyle, S.J., Howard, C.M., Haldeman, A., and Neubaum, J., “Computed Tomography Scanning and Geophysical Measurements of Appalachian Basin Core from the Jones and Laughlin #1 Well, Beaver County, PA,” NETL-PUB-3889, NETL Technical Report Series, U.S. Department of Energy, National Energy Technology Laboratory, Morgantown, WV, 2023, p. 36, https://edx.netl.doe.gov/dataset/ct-scanning-and-gm-of-appalachian-basin-core-from-the-jonesand-laughlin-1-well-beaver-county-pa, DOI: 10.2172/1995971.

Computed Tomography Scanning and Petrophysical Measurements of the Lively Grove #1 Well Core

Crandall, D., Paronish, T., Mitchell, N., Jarvis, K., Brown, S., Moore, J., Gill, M., Blakley, C., Okwen, R., Korose, C., and Carman, C., “Computed Tomography Scanning and Petrophysical Measurements of the Lively Grove #1 Well Core,” NETL-PUB-3877, NETL Technical Report Series, U.S. Department of Energy, National Energy Technology Laboratory, Morgantown, WV, 2023, p. 60, https://edx.netl.doe.gov/dataset/computed-tomography-scanning-and-petrophysicalmeasurements-of-the-lively-grove-1-well-core, DOI: 10.2172/1989188.

Computed Tomography Scanning and Geophysical Measurements of the CarbonSAFE Seal Integrity Wells in the Illinois Basin

Paronish, T., Mitchell, N., Brown, S., Pohl, M., Crandall, D., Blakley, C., Korose, C., and Okwen, R., “Computed Tomography Scanning and Geophysical Measurements of the CarbonSAFE Seal Integrity Wells in the Illinois Basin,” DOE/NETL-2023/4323; NETL Technical Report Series, U.S. Department of Energy, National Energy Technology Laboratory, Morgantown, WV, (2023), p. 68, DOI: https://doi.org/10.2172/1962306.

Computed Tomography Scanning and Geophysical Measurements of the One Earth Energy Well #1 Core

Crandall, D., Gill, M., Paronish, T., Brown, S., Mitchell, N., Jarvis, K., Moore, J., Blakley, C., Okwen, R., Korose, C., and Carman, C., “Computed Tomography Scanning and Geophysical Measurements of the One Earth Energy Well #1 Core,” DOE.NETL-2023.3847; NETL Technical Report Series, U.S. Department of Energy, National Energy Technology Laboratory, Morgantown, WV, (2023), p 60. https://doi.org/10.2172/1963265.

A Framework to Simulate the Blowout of CO2 Through Wells in Geologic Carbon Storage

Bhuvankar, P.; Cihan, A.; Birkholzer, J. A Framework to Simulate the Blowout of CO2 Through Wells in Geologic Carbon Storage. International Journal of Greenhouse Gas Control, 2023, 127, Article 103921, ISSN 1750-5836. https://doi.org/10.1016/j.ijggc.2023.103921.

Evaluation of the Economic Implications of Varied Pressure Drawdown Strategies Generated Using a Real-time, Rapid Predictive, Multi-Fidelity Model for Unconventional Oil and Gas Wells

Bello, K., Vikara, D., Sheriff, A., Viswanathan, H., Carr, T., Sweeney, M., O’Malley, D., Marquis, M., Vactor, R.T., and Cunha, L., “Evaluation of the Economic Implications of Varied Pressure Drawdown Strategies Generated Using a Real-time, Rapid Predictive, Multi-Fidelity Model for Unconventional Oil and Gas Wells,” Gas Science and Engineering, (2023) https://doi.org/10.1016/j.jgsce.2023.204972.

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

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