Bauer, J., Justman, D., and Rose. K. Invited presentation. Machine Learning Clustering to Identify Natural Gas Pipeline Infrastructure Vulnerabilities. Department of Homeland Security Science & Technology Directorate 2021 Big Data Series Workshop, March 24, 2021. https://www.osti.gov/biblio/1814179
disCO2ver
Unlocking data-driven capabilities for the entire CTS community
Bibliographies
ML Clustering to Identify Natural Gas Pipeline Infrastructure Vulnerabilities
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
Tools for Data Collection, Curation, and Discovery to Support Carbon Storage Insights
Mark-Moser, M., Rose, K., Baker, V. D. (2020, December 17). Tools for Data Collection, Curation, and Discovery to Support Carbon Storage Insights. [Conference presentation]. Session: IN042 – Utilizing unstructured data in Earth Science Poster Session. https://ui.adsabs.harvard.edu/abs/2020AGUFMIN0140002M/abstract
NRAP-Open-IAM: A New, Open-Source Code for Integrated Assessment of Geologic Carbon Storage Containment Effectiveness and Leakage Risk
Vasylkivska, V., Bacon D., Chen, Bailian, Dilmore R., Harp D., King S., Lackey G., Lindner E., Liu Guoxiang, Mansoor K., Zhang Yingqi. NRAP-Open-IAM: A New, Open-Source Code for Integrated Assessment of Geologic Carbon Storage Containment Effectiveness and Leakage Risk. AGU Annual Fall Meeting (Virtual), 2020 Session: GC110. Advances in Computational Methods for Geologic CO2 Sequestration I eLightning. https://ui.adsabs.harvard.edu/abs/2020AGUFMGC110..10V/abstract
Developing a structured seafloor sediment database from disparate datasets using SmartSearch
Mark-Moser, M., Rose, K., Baker, V. D. 2020. Developing a structured seafloor sediment database from disparate datasets using SmartSearch. AGU Annual Fall Meeting (Virtual), 2020. Session: IN042 – Utilizing unstructured data in earth science https://www.osti.gov/servlets/purl/1776797
Probabilistic Machine Learning for Integrated Social-Natural-Physical Assessment
Ghanem, R., Zhang, R., Rose, K., invited talk, Probabilistic Machine Learning for Integrated Social-Natural-Physical Assessment, AGU Annual Meeting 2020, Session: H027 – Artificial Intelligence and Machine Learning for Multiscale Model-Experimental Integration https://agu.confex.com/agu/fm20/prelim.cgi/Session/103051
Deep Learning to Locate Seafloor Landslides in High Resolution Bathymetry
Dyer, A., Zaengle, D., Mark-Moser, M., Duran, R., Suhag, A., Rose, K., Bauer, J. Deep Learning to Locate Seafloor Landslides in High Resolution Bathymetry. AGU Annual Fall Meeting (Virtual), 2020. Session: NH007 – Data Science and Machine Learning for Natural Hazard Sciences II Posters. https://www.osti.gov/servlets/purl/1779617
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
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.
National Risk Assessment Partnership: Tools and Recommended Practices for Induced Seismicity Risk Management
White, J. (2022). NRAP: Tools and Recommended Practices for Induced Seismicity and Risk Management. 2022 Carbon Management Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/22CM_CTS18_White.pdf
National Risk Assessment Partnership: Phase II Key Accomplishments and Phase III Introduction
Dilmore, R. (2022). National Risk Assessment Partnership: Phase II Accomplishments and Phase III Introduction. 2022 Carbon Management Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/22CM_CTS18_Dillmore.pdf
An Updated Carbon Storage Open Database – Geospatial Data Aggregation to Support Scaling up CCS
Morkner, P. (2022). An Updated Carbon Storage Open Database – Geospatial Data Aggregation to Support Scaling up CCS. 2022 Carbon Management Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/22CM_CTS17_Morkner.pdf
Advanced Data Extraction to Support a Living Database
Sabbatino, M. (2022). Advanced Data Extraction to Support a Living Database. 2022 Carbon Management Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/22CM_CTS17_Sabbatino.pdf
Geo-Data Science Driven Insights Into CCS EJ/SJ Opportunities in Support of Energy Community Transitions
Bauer, J. (2022). Geo-Data Science Driven Insights into CCS EJ/SJ Opportunities in Support of Energy Community Transitions. 2022 Carbon Management Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/22CM_CTS17_Bauer.pdf
The DisCO2ver Platform, Building a Virtual Carbon Storage Data Laboratory and Infrastructure for the Future
Rose, K. Morkner, P. Bauer, J. (2022). The disCO2ver Platform, Building a Virtual Carbon Storage Data Laboratory and Infrastructure for the Future. 2022 Carbon Management Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/22CM_CTS17_Rose.pdf
DOE Offshore Carbon Storage Saline Calculator Methodology and Tool
Romeo, L. Rose, K. Bauer, J. Mark-Moser, M. Bean, A. Thomas, B. (2022). Offshore CO2 Saline Storage Methodology and Calculator. 2022 Carbon Management Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/22CM_CTS17_Romeo.pdf
Site Selection and Cost Estimation of Pilot-Scale CO2 Saline Storage Study in the Gulf of Mexico
Wijaya, N. Vakara, D. Bello, K. Vactor, T. Grant, T. Morgan, D. (2022). Site Selection and Cost Estimation for Pilot-Scale CO2 Saline Storage Study in the Gulf of Mexico. 2022 Carbon Management Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/22CM_CTS17_Wijaya_2.pdf
Updating NATCARB and Carbon Storage Geospatial Resources via EDX Cloud
Morkner, P., Bauer, J., Pantaleone, S., Shay, J., Rowan, C., Baker, V., Obradovich, J., and Rose, K. Updating NATCARB and Carbon Storage Geospatial Resources via EDX Cloud. U.S Department of Energy National Energy Technology Laboratory Carbon Management Project Review Meeting, August 16th, 2022. https://netl.doe.gov/sites/default/files/netl-file/22CM_CTS16_Morkner.pdf
AIIM: Advanced Infrastructure Integrity Modeling
Bean, A., Romeo, L., Bauer, J. AIIM: Advanced Infrastructure Integrity Modeling. TechConnect. June 13-15, 2022. National Harbor, D.C. https://www.osti.gov/biblio/1890422