Romeo, L. (2021, August 9). Assessing Current & Future Infrastructure Hazards: Forecasting Integrity using Machine Learning & Advanced Analytics [Conference presentation]. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/20VPRONG_26_Romeo.pdf
disCO2ver
Unlocking data-driven capabilities for the entire CTS community
Bibliographies
Assessing Current & Future Infrastructure Hazards: Forecasting Integrity using Machine Learning & Advanced Analytics
NETL’s SmartSearch Deep Learning Tool
Baker, V., Bauer, J., Morkner, P., Rose, K. NETL’s SmartSearch Deep Learning Tool – Scalable data search and parse for carbon storage data discovery. Carbon Management and Oil and Gas Research Project Review Meeting – Carbon Storage. August 9th, 2021. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Baker9.pdf
Examining Possible CCS Deployment Pathways: Onshore and Offshore (FWP-1022464)
Grant, T. (2021, August 9). Examining Possible CCS Deployment Pathways: Onshore and Offshore. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Grant6.pdf
National Risk Assessment Partnership: NRAP Tools and Recommended Practices for Containment Assurance and Leakage Risk Management
Bacon, D. Pawar, R. (2021, August 9). NRAP Tools and Recommended Practices for Containment Assurance and Leakage Risk Management. [Conference presentation]. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Bacon6.pdf
National Risk Assessment Partnership: NRAP Tools and Recommended Practices for Induced Seismicity
White, J. Templeton, D. (2021, August 9). National Risk Assessment Partnership: NRAP Tools and Recommended Practices for Induced Seismicity [Conference presentation]. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_White6_0.pdf
NRAP Phase II – Managing Risks and Reducing Uncertainties: An Overview of Research Objectives and Accomplishments
Dilmore, R. Gasperikova, E. Thomas, B. (2021, August 6). NRAP Phase II – Managing Risks and Reducing Uncertainties: An Overview of Research Objectives and Accomplishments [Conference presentation]. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Dilmore6.pdf
SMART: Real Time Visualization for Rock and Fluid Properties
Crandall, D. Alumbaugh, D. (2021, August 6). SMART: Real Time Visualization for Rock and Fluid Properties. [Conference presentation]. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Crandall6.pdf
Carbon Storage Data Integration, Visualization, and Application via EDX and GeoCube
Morkner, P. Bauer, J. Rowan, C. Barkhurst, A. Rose, K. (2021). Carbon Storage Data Integration, Visualization, and Application via EDX and Geocube. 2021 Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Morkner6.pdf
SMART: Real Time Visualization for Pressure and Stress
White, J. (2021). SMART: Real Time Visualization of Pressure and Stress. 2021 Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_White6.pdf
Using SmartParse NLP Tools to Develop a Living Database for Carbon Storage Data
Morkner, P. Sabbatino, M. (2021, August 9). Using SmartParse NLP Tools to Develop a Living Database for Carbon Storage Data [Conference presentation]. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Morkner5.pdf
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.
Data Curation for Basin-Scale Modeling in NRAP Phase III
Morkner, P., and Zhou, Q. Data Curation for Basin-Scale Modeling in NRAP Phase III. National Risk Assessment Partnership Annual Technical Meeting, May 2022. Oral Presentation. https://www.osti.gov/servlets/purl/1891859
Development of Machine Learning Models for Full Field Reservoir Characterization
Wu, X., Shih, C., Mark-Moser, M., and Wingo, P., 2021. Development of machine learning models for full field Reservoir Characterization. AGU Fall Meeting 2021, Dec. 13-17, New Orleans, LA/Virtual. Session H34D – Application of Multimodal Physics-Informed Machine Learning/Deep Learning in Subsurface Flow and Transport Modeling. https://www.osti.gov/servlets/purl/1846178
Science-based Artificial Intelligence and Machine Learning (AI/ML) Institute (SAMI) – Accelerating Cross-Disciplinary AI/ML for Applied Geoscience, Energy, and Environmental Challenges
Shih, C., Thornton, J., Rose, K., Syamlal, M., Bromhal, G., Guenther, C., Pfautz, J., Van Essendelft, D., and Bauer, J., 2021, Science-based Artificial Intelligence and Machine Learning (AI/ML) Institute (SAMI) – accelerating cross-disciplinary AI/ML for applied geoscience, energy, and environmental challenges. AGU Fall Meeting 2021, Dec. 13-17, New Orleans, LA/Virtual. Session: IN12A – Growing Opportunities for Multiparty Collaborations in Artificial Intelligence and Machine Learning for Science Research. https://ui.adsabs.harvard.edu/abs/2021AGUFMIN12A..05S/abstract
Improving Prediction of Subsurface Properties Using a Geoscience Informed, Multi-Technique, Artificial Intelligence Approach
Rose, K., Mark-Moser, M., Suhag, A., and Bauer, J. 2021. Improving prediction of subsurface properties using a geoscience informed, multi-technique, artificial intelligence approach (Invited). AGU Fall Meeting 2021, Dec. 13-17, New Orleans, LA/Virtual. Session H33C – Application of Multimodal Physics-Informed Machine Learning/Deep Learning in Subsurface Flow and Transport Modeling. https://ui.adsabs.harvard.edu/abs/2021AGUFM.H33C..01R/abstract
Leveraging Data Ecosystems to Support Earth Science Research for Decarbonization
Morkner, P., Mark-Moser, M., Justman, D., Rowan, C., Bauer, J., and Rose, K., 2021. Leveraging Data Ecosystems to Support Earth Science Research For Decarbonization. AGU Fall Meeting 2021, Dec. 13-17, New Orleans, LA/Virtual. Session U21A-07 – How Earth Science Research Can Help Accelerate the Transition to a Decarbonized Economy. https://ui.adsabs.harvard.edu/abs/2021AGUFM.U21A..07M/abstract
Exploring Subsurface Data Availability on the Energy Data eXchange (EDX)
Morkner, P., Bean, A., Bauer, J., Barkhurst, A., and Rose, K.. 2021. Exploring subsurface data availability on the Energy Data eXchange. AGU Fall Meeting 2021, Dec. 13-17, New Orleans, LA/Virtual. Session: SY039 – Subsurface Storage of Natural Gas, CO2, and Hydrogen: Key Learnings and Future Opportunities. https://www.osti.gov/servlets/purl/1846774
AI/ML Integration for Accelerated Analysis and Forecast of Offshore Hazards
Mark-Moser, M., Wingo, P., Duran, R., Dyer, A., Zaengle, D., Suhag, A., Hoover, B., Pantaleone, S., Shay, J., Bauer, J., and Rose, K. 2021. AI/ML integration for accelerated analysis and forecast of offshore hazards. AGU Fall Meeting 2021, Dec. 13-17, New Orleans, LA/Virtual. Session: EP027 – Proven AI/ML applications in the Earth Sciences. https://www.osti.gov/servlets/purl/1846789
On the Predictability of Loop Current Eddy Shedding Events and Unexpected Links to the Brazil and Guiana Currents
Duran, R., Liang, X.S., Allende-Arandia, M.E., Appendini, C.M., Mark-Moser, M., Rose, K., Bauer, J. 2021. On the predictability of Loop Current Eddy Shedding events and unexpected links to the Brazil and Guiana Currents. AGU Fall Meeting 2021, Dec. 13-17, New Orleans, LA/Virtual. Session: OS45D – Ocean Dynamics of the Gulf of Mexico III Poster. https://www.osti.gov/servlets/purl/1846777
Evaluating the Effects of a Low-Carbon Energy Transition on Existing U.S. Fossil Energy Communities
Bauer, J., Rose, K., Romeo, L., Justman, D., Hoover, B., and B. White. 2021. Evaluating the effects of a low-carbon energy transition on existing U.S. fossil energy communities. AGU Fall Meeting 2021, Dec. 13-17, New Orleans, LA/Virtual. Session GC25G: Environmental Justice/Equity and Global Change: Methodologies, Frameworks, and Results II Poster. https://ui.adsabs.harvard.edu/abs/2021AGUFMGC25G0722B/abstract
Forecasting 3D Structural Complexity with AI/ML method: Mississippi Canyon, Gulf of Mexico
Pantaleone, S., Mark Moser, M., Bean, A., Walker, S., Rose, K., 2021, “Forecasting 3D Structural Complexity with AI/ML method: Mississippi Canyon, Gulf of Mexico”. AAPG/SEG IMAGE conference, Denver, Colorado, September 26, 2021 October 1, 2021. https://edx.netl.doe.gov/sites/offshore/forecasting-3d-structural-complexity-with-ai-ml-method-mississippi-canyon-gulf-of-mexico/