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.
disCO2ver
Unlocking data-driven capabilities for the entire CTS community
Bibliographies
Computed Tomography Scanning and Geophysical Measurements of the CarbonSAFE Seal Integrity Wells in the Illinois Basin
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 Anonymization Tool Integration into DisCO2ver
Morkner, P., Bauer, J., Hoover, B., Wingo, P., Gao, M., Sharma, M., Neumann, C., Johnson, C., and Schuetter, J., “Data Anonymization Tool Integration into DisCO2ver,” presented at the Carbon Storage BIL Workshop on May 2, 2023.
Class VI Data Support Tool
Morkner, P., Strazisar, B., Pantaleone, S., Schooley, S., Shay, J., Pfander, I., and Rose, K., “Class VI Data Support Tool,” presented at the Carbon Storage BIL Workshop on May 2, 2023.
A Quantitative Risk Assessment Approach for Developing Contingency Plans at a Geologic Carbon Storage Site
Mitchell, N.; Lackey, G.; Schwartz, B.; Strazisar, B.; Dilmore, R. A Quantitative Risk Assessment Approach for Developing Contingency Plans at a Geologic Carbon Storage Site. Greenhouse Gases: Science and Technology 2023, 13(3), 320-339. https://doi.org/10.1002/ghg.2219.
Evaluating Probability of Containment Effectiveness at a GCS Site using Integrated Assessment Modeling Approach with Bayesian Decision Network
Wang, Z.; Dilmore, R. M.; Bacon, D. H.; Harbert, W. Evaluating Probability of Containment Effectiveness at a GCS Site using Integrated Assessment Modeling Approach with Bayesian Decision Network, Greenhouse Gases: Science and Technology, 2021, 11(2), 360-376. https://doi.org/10.1002/ghg.2056.
Developing a Nationally Integrated and Publicly Available Oil and Gas Well Database to Inform Safe Carbon Storage & Infrastructure Reuse Opportunities
Romeo, L., Pfander, I., Amrine, D., Sabbatino, M., Sharma, M., Tetteh, D., Rose, K., and Bauer, J., “Developing a Nationally Integrated and Publicly Available Oil and Gas Well Database to Inform Safe Carbon Storage & Infrastructure Reuse Opportunities,” CCUS 2024 SPE AAPG SEG, Houston, TX, March 11–13, 2024.
Modeling‐Based Assessment of Deep Seismic Potential Induced by Geologic Carbon Storage
Chang, K.W., and Yoon, H., “Modeling‐Based Assessment of Deep Seismic Potential Induced by Geologic Carbon Storage,” Seismological Research Letters, 49(3), 1447–1454, (2023) https://doi.org/10.1785/0220220365.
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.
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 Geospatial Analytical Framework to Identify Seafloor Geohazards in the Northern Gulf of Mexico
Duran, R., Dyer, A., Mark-Moser, M., Bauer, J., Rose, K., Zaengle. D., Wingo, P. 2020. A Geospatial Analytical Framework to Identify Seafloor Geohazards in the Northern Gulf of Mexico. AGU Annual Meeting 2020, Session: NH010 – Geohazards in Marine and Lacustrine Environments. https://ui.adsabs.harvard.edu/abs/2020AGUFMNH004..08D/abstract
Optimizing Prediction of Reservoir Properties with Artificial Intelligence, Big Data, and the Subsurface Trend Analysis Method
Mark-Moser, M., Suhag, A., Rose, K., Wingo, P. (2020, November 9). Optimizing prediction of reservoir properties with artificial intelligence, big data, and the Subsurface Trend Analysis method [Conference presentation]. Machine Learning for Oil and Gas 2020, Nov. 9-11, Virtual. https://edx.netl.doe.gov/sites/offshore/optimizing-prediction-of-reservoir-properties-with-artificial-intelligence-big-data-and-the-subsurface-trend-analysis-method/
Advanced Geospatial Analytics and Machine Learning for Offshore and Onshore Oil & Natural Gas Infrastructure
Justman D., Romeo, L., Barkhurst, A., Bauer, J., Duran, R., Dyer, A., Nelson, J., Sabbatino, M., Wingo, P., Wenzlick, M., Zaengle, D., Rose, K. (2020, October 6-7). Advanced geospatial analytics and machine learning for offshore and onshore oil & natural gas infrastructure. [Virtual conference presentation]. GIS Week 2020. https://www.osti.gov/servlets/purl/1767074
Enhancing Knowledge Discovery of Unstructured Data to Support Context in Subsurface-Modeling Predictions
Hoover, B., Mark-Moser, M., Wingo, P., Suhag, A., Rose, K. 2021. Enhancing knowledge discovery of unstructured data to support context in subsurface-modeling predictions. ACE/SEG21, Denver, Colorado, Sept. 26th-Oct. 1st. https://www.osti.gov/servlets/purl/1843422
Using AI/ML to Curate Thousands of Carbon Storage Data Assets via EDX
Morkner, P., Rowan, C., Rose, K., Bauer, J., Sabbatino, M., Barhurst, A. Using AI/ML to Curate Thousands of Carbon Storage Data Assets via EDX. NETL Carbon Storage Review Meeting. September 10, 2020. Virtual. https://netl.doe.gov/sites/default/files/netl-file/20CSVPR_Morkner.pdf
Assessing Offshore CO2 Saline Storage Potential with the NETL Calculator
Romeo, L., Rose, K., Thomas, R., Mark-Moser, M., Barkhurst, A., Wingo, P., Bean, A. 2020. Assessing Offshore CO2 Saline Storage Potential with the NETL Calculator. Carbon Storage Review Meeting. September 11, 2020. Virtual. https://netl.doe.gov/sites/default/files/netl-file/20CSVPR_Romeo_11.pdf
Building an Analytical Framework to Measure Offshore Infrastructure Integrity, Identify Risk, and Strategize Future Use for Oil and Gas
Dyer, A., Romeo, L., Wenzlick, M., Bauer, J., Nelson, J., Duran, R., Zaengle, D., Wingo, P., and Sabbatino, M. 2020. Building an Analytical Framework to Measure Offshore Infrastructure Integrity, Identify Risk, and Strategize Future Use for Oil and Gas. Esri User Conference, San Diego, CA, July 13-15, 2020. https://www.osti.gov/servlets/purl/1604638
Harnessing the Power of DOE Data Computing for End-user Analytics, SMART Webinar
Rose, K., Barkhurst, A., Mark-Moser, M., Romeo, L., and Wingo, P., 2020, Harnessing the Power of DOE Data Computing for End-user Analytics, SMART Webinar 6/25/2020, https://www.youtube.com/watch?v=G5oUWSb-kHc&feature=youtu.be