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Bibliographies

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

Geohazard Analysis Gulf of Mexico Offshore Seafloor

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/

AI/ML Offshore Reservoir Properties Subsurface Trend Analysis

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

AI/ML Geospatial Analytics Natural Gas Infrastructure NETL Carbon Storage Program

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

Modeling NETL Carbon Storage Program Prediction Subsurface Data

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

AI/ML Carbon Storage Data Curation NETL Carbon Storage Program

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

Calculator Offshore Saline Storage

Exploring Beneath the Basemap

Bauer, J., Justman, D., Mark-Moser, M., Romeo, L., Creason, C.G., and Rose, K., “Exploring Beneath the Basemap,” GIS for Science: Applying Mapping and Spatial Analytics, Vol. 2 (2020), pp. 51–67.

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

Offshore Offshore Infrastructure Integrity Oil and Gas Risk Assessment

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

Offshore Risk Modeling Risk Prevention

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

Offshore Oil Spills Spatial Tool

Rules and Tools Crosswalk: A Compendium of Computational Tools to Support Geologic Carbon Storage Environmentally Protective UIC Class VI Permitting

Lackey, G.; Strazisar, B. R.; Kobelski, B.; McEvoy, M.; Bacon, D. H.; Cihan, A.; Iyer, J.; Livers-Douglas, A.; Pawar, R.; Sminchak, J.; Wernette, B.; Dilmore, R. M. Rules and Tools Crosswalk: A Compendium of Computational Tools to Support Geologic Carbon Storage Environmentally Protective UIC Class VI Permitting; NRAP-TRS-I-001-2022; DOE.NETL-2022.3731; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Pittsburgh, PA, 2022; p 120. DOI: https://doi.org/10.2172/1870412

Computational Tools NRAP Permit Application UIC Class VI Permit

Applied machine learning model comparison: Predicting offshore platform integrity with gradient boosting algorithms and neural networks

Dyer, A.S., Zaengle, D., Nelson, J.R., Duran, R., Wenzlick, M., Wingo, P.C., Bauer, J.R., Rose, K., and Romeo, L. (2022). Applied machine learning model comparison: Predicting offshore platform integrity with gradient boosting algorithms and neural networks, Marine Structures, Volume 83, 103152. https://doi.org/10.1016/j.marstruc.2021.103152.

Geo-Data Science Machine Learning Offshore

Bayesian Approach for In-Situ Stress Prediction and Uncertainty Quantification for Subsurface Engineering

Bao, T.; Burghardt, J. A. Bayesian Approach for In-Situ Stress Prediction and Uncertainty Quantification for Subsurface Engineering. Rock Mechanics and Rock Engineering 2022, 55, 4531–4548. https://doi.org/10.1007/s00603-022-02857-0.

3D Distribution of Stress In-Situ Stress Prediction NRAP Subsurface Engineering

Thermal and solubility effects on fault leakage during geologic carbon storage

Meguerdijian, S.; Pawar, R. J.; Harp, D. R.; Jha, B. Thermal and solubility effects on fault leakage during geologic carbon storage. International Journal of Greenhouse Gas Control 2022, 116, Article 103633. https://doi.org/10.1016/j.ijggc.2022.103633.

CO2 Leakage Geologic Carbon Storage NRAP Reduced-Order Models (ROM)

Leakage from Coexisting Geologic Forcing and Injection-Induced Pressurization: A Semi-Analytical Solution for Multilayered Aquifers with Multiple Wells

Cihan, A.; Oldenburg, C. M.; Birkholzer, J. T. Leakage from Coexisting Geologic Forcing and Injection-Induced Pressurization: A Semi-Analytical Solution for Multilayered Aquifers with Multiple Wells. Water Resources Research 2022, 58 (5), e2022WR032343. https://doi.org/10.1029/2022WR032343.

CO2 Injection CO2 Leakage Induced Seismicity Risk NRAP

Coupled hydromechanical modeling of induced seismicity from CO2 injection in the Illinois Basin

Luu, K.; Schoenball, M.; Oldenburg, C. M.; Rutqvist, J. Coupled hydromechanical modeling of induced seismicity from CO2 injection in the Illinois Basin. Journal of Geophysical Research: Solid Earth 2022, 127(5), e2021JB023496. https://doi.org/10.1029/2021JB023496.

CO2 Injection Illinois Basin Induced Seismicity NRAP

Monitoring Geologic Carbon Sequestration Using Electrical Resistivity Tomography

Yang, X.; Carrigan, C. Monitoring Geologic Carbon Sequestration Using Electrical Resistivity Tomography, Geophysical Monitoring for Geologic Carbon Storage, Huang, L. (Ed.), 2022, 255-271. https://doi.org/10.1002/9781119156871.ch16.

CO2 Leakage Electrical Resistivity Tomography Geologic Carbon Storage NRAP

Monitoring Carbon Storage Sites With Time-Lapse Gravity Surveys. Geophysical Monitoring for Geologic Carbon Storage

Appriou, D.; Bonneville, A. (2022). Monitoring Carbon Storage Sites With Time-Lapse Gravity Surveys. Geophysical Monitoring for Geologic Carbon Storage, Huang, L. (Ed.), 2022, 211-232. https://doi.org/10.1002/9781119156871.ch14.

CO2 Behavior Gravity Detection Monitoring Carbon Storage NRAP

Fundamentals of Electrical and Electromagnetic Techniques for CO2 Monitoring

Gasperikova, E.; Morrison, H. F. Fundamentals of Electrical and Electromagnetic Techniques for CO2 Monitoring. Geophysical Monitoring for Geologic Carbon Storage, Huang, L. (Ed.), 2022, 233-253. https://doi.org/10.1002/9781119156871.ch15.

CO2 Injection Electrical and Electromagnetic Methods Geologic Carbon Storage NRAP

Automatic Waveform Quality Control for Surface Waves Using Machine Learning

Chai, C., Kintner, J.A., Cleveland, K.M., Luo, J., Maceira, M., and Charles J. Ammon, C.J., “Automatic Waveform Quality Control for Surface Waves Using Machine Learning,” Seismological Research Letters, 93(3), 1683-1694, (2022) https://doi.org/10.1785/0220210302.

Automatic Waveform Quality Machine Learning SMART Surface Waves

Adaptive, Risk-Based Monitoring of Geologic Carbon Storage

Gasperikova, E. Vasylkivska, V. Yang, X. Huang, L. Hanna, A. Chen, B. Creasy, N. Li, D. Blatter, D. Kumar, A. Dilmore, R. Harbert, B. Morgan, D. Iyer, J.K. Smith, M. Kirol, A. Appriou, D. (2023, August 31). Adaptive, Risk-Based Monitoring of Geologic Carbon Storage [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS31_Gasperikova.pdf

FECM/NETL Carbon Management Meeting Geologic Carbon Storage (GCS)NRAP RAMP Tool Risk-Based Monitoring

NRAP Phase III Overview: Objectives and Progress

Dilmore, R. (2023, August 31). NRAP Phase III Overview: Objectives and Progress [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS31_Dilmore.pdf

FECM/NETL Carbon Management Meeting NRAP Phase III Risk Assessment

Anonymizing Sensitive Carbon Storage Data Tool

Morkner, P. Bauer, J. Wingo, P. Gao, M. Sharma, M. Hoover, B. Neumann, C. Johnson, C. Schuetter, J. Rose, K. (2023, August 29). Anonymizing Sensitive Carbon Storage Data Tool [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS29_Morkner.pdf

Carbon Storage Data Data Anonymization EDX4CCS FECM/NETL Carbon Management Meeting Geospatial and Information Substitution and Anonymization Tool (GISA)

A Comprehensive Dashboard for CS Planning

Justman D. Pantaleone, S. Sharma, M. Romeo, L. Morkner, P. Bauer, J. (2023, August 29). A Comprehensive Dashboard for CS Planning [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS29_Justman.pdf

Carbon Storage Data Carbon Storage Planning Framework Dashboard EDX4CCS EJ/SJ FECM/NETL Carbon Management Meeting

EDX Cloud Optimization for Carbon Management

Rose, K. Baker, V. (2023, August 28). EDX Cloud Optimization for Carbon Management [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS28_Rose.pdf

AI R&D Carbon Management Cloud Computing EDX/SAMI FECM/NETL Carbon Management Meeting

Licensing and Virtualizing Carbon Storage Models and Tools via EDX disCO2ver

Zaengle, D. Sinclair, J. Wingo, P. Rowan, C. Rose, K. (2023, August 28). Licensing and Virtualizing Carbon Storage Models and Tools via EDX disCO2ver [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS28_Zaengle.pdf

Carbon Storage EDX disCO2ver EDX++EDX4CCS FECM/NETL Carbon Management Meeting

EDX++: Migrating EDX to the Cloud, Unlocking Next-Generation Data Infrastructure

Baker, V. Rose, K. Obradovich, J. McFarland, D. Jones, TJ. Mondello, J. Dean, E. Sarle, J. (2023, August 28). EDX++: Migrating EDX to the Cloud, Unlocking Next-Generation Data Infrastructure [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS28_Baker.pdf

Data Infrastructure EDX++FECM/NETL Carbon Management Meeting Multi-Cloud SAMI

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

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

EDX4CCS FECM/NETL Carbon Management Meeting Geologic Carbon Storage (GCS)National Structural Complexity Database Saline Basins

Managing Carbon Storage Data With a Living Database

Sabbatino, M. Morkner, P. Choisser, A. Leveckis, S. Bauer, J. Rose, K. (2023, August 28). Managing Carbon Storage Data With a Living Database [Poster presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTSp_Sabbatino.pdf

EDX Spatial EDX++FECM/NETL Carbon Management Meeting Geologic Carbon Storage (GCS)Living Database

Machine Learning Based Fracture Network Quantification at the IBDP CO2 Sequestration Site

Kumar, A. Harbert, W. Liu, G. Myshakin, E.(2023, August 28). Machine Learning Based Fracture Network Quantification at the IBDP CO2 Sequestration Site [Poster presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTSp_Kumar.pdf

FECM/NETL Carbon Management Meeting Fracture Network Mapping Machine Learning Microseismic Data SMART