Romeo, L., Leveckis, S., Houghton, B., Gao, M. C., Zaengle, D., Schooley, C., Rose, K., and Bauer, J., “An Open-Source, Machine Learning-Informed, Geospatial-Driven Tool for Identifying and Evaluating CO2 Transport Routes,” SPE AAPG SEG CCUS 2025, Houston, TX, March 3–5, 2025.
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An Open-Source, Machine Learning-Informed, Geospatial-Driven Tool for Identifying and Evaluating CO2 Transport Routes
Analog Selection and Project Comparison Using Offshore Carbon Storage Project Inventory and Data
Mulhern, J.S., Mark-Moser, M., and Rose, K., “Analog Selection and Project Comparison Using Offshore Carbon Storage Project Inventory and Data,” accepted for SPE AAPG SEG CCUS 2025, Houston, TX, March 3–5, 2025.
Extending Compliance Inspection Data with Predictive Modeling for Marginal Conventional Wells with Emissions in New York State
Dyer, A., Schooley, C., White, C., Wise, J., and Lackey, G., “Extending Compliance Inspection Data with Predictive Modeling for Marginal Conventional Wells with Emissions in New York State,” conference abstract from AGU Annual Meeting 2024, Washington, DC, December 9–13, 2024.
CO2-Locate: A Dynamic Database and Tool for Accessing National Oil and Gas Well Data to Inform Carbon Storage Projects
Dyer, A., Pfander, I., Tetteh, D., Cleaveland, C., Sabbatino, M., Romeo, L., Bauer, J., and Rose, K., “CO2-Locate: A Dynamic Database and Tool for Accessing National Oil and Gas Well Data to Inform Carbon Storage Projects,” conference abstract from AGU Annual Meeting 2024, Washington, DC, December 9–13, 2024.
The Carbon Storage Planning Inquiry Tool (CS PlanIT)
Morkner, P., Pantaleone, S., Rich, M., Justman, D., and Rose, K. “The Carbon Storage Planning Inquiry Tool (CS PlanIT)”. US Energy Administration Seminar. November, 2024. Online.
Carbon Storage Technical Viability Approach (CS TVA) Matrix: Integrating Multiple Components for Comprehensive Scoping and Data Availability Assessments
Mulhern, J.S., Mark-Moser, M., Creason, C.G., Maymi, N., Shay, J., Lara, A., and Rose, K., “Carbon Storage Technical Viability Approach (CS TVA) Matrix: Integrating Multiple Components for Comprehensive Scoping and Data Availability Assessments,” AAPG Rocky Mountain Elevating Energy Section Meeting, Park City, UT, October 6–8, 2024.
Where are the Data? Automating a Workflow for Carbon Storage Data Gap Analysis
Creason, C.G., Mulhern, J.S., Cordero Rodriguez, N., Mark-Moser, M., Lara, A., Shay, J., and Rose, K. Where are the Data? Automating a Workflow for Carbon Storage Data Gap Analysis, Geological Society of America Connects Annual Meeting. Anaheim, CA. September 22-25, 2024.
Carbon Storage Technical Viability Approach (CS TVA) Matrix: Integrating Multiple Components for Comprehensive Scoping
Mulhern, J.S., Mark-Moser, M., Creason, C.G., Maymi, N., Shay, J., Lara, A., and Rose, K., “Carbon Storage Technical Viability Approach (CS TVA) Matrix: Integrating Multiple Components for Comprehensive Scoping,” Geological Society of America CONNECTS Annual Meeting, Anaheim, CA, September 22–25, 2024.
Offshore Carbon Storage Data Collection and International Offshore Carbon Storage Project Inventory
Mulhern, J.S., Mark-Moser, M., and Rose, K., “Offshore Carbon Storage Data Collection and International Offshore Carbon Storage Project Inventory,” Geological Society of America CONNECTS Annual Meeting, Anaheim, CA, September 22–25, 2024.
International Offshore Geologic Carbon Storage Project Inventory and Data Collection
Mulhern, J.S., Mark-Moser, M., and Rose, K. “International Offshore Geologic Carbon Storage Project Inventory and Data Collection”. Seventh International Offshore Geologic CO2 Storage Workshop. Port Arthur, Texas. September 17-19, 2024. Invited.
NRAP-Open-IAM: Open Wellbore Component v2.0
Bacon D. H.; Pan, L.; Oldenburg, C. M. NRAP-Open-IAM: Open Wellbore Component v2.0, 2021. PNNL-31543. Richland, WA: Pacific Northwest National Laboratory. https://doi.org/10.2172/1825929.
Stress Controls Rupture Extent and Maximum Magnitude of Induced Earthquakes
Kroll, K. A.; Cochran, E. S. Stress Controls Rupture Extent and Maximum Magnitude of Induced Earthquakes. Geophysical Research Letters 2021, 48(11), e2020GL092148. https://doi.org/10.1029/2020GL092148.
Sealing of Fractures in a Representative CO2 Reservoir Caprock by Migration of Fines
Rod, K.A.; Cantrell, K.J.; Varga, T.; Battu, A.; Brown, C.F. Sealing of Fractures in a Representative CO2 Reservoir Caprock by Migration of Fines. Greenhouse Gases: Science and Technology 2021. 11(3), 483-492. PNNL-SA-160332, https://doi.org/10.1002/ghg.2061.
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
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
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.
A systematic, science-driven approach for predicting subsurface properties
Rose, K., Bauer, J.R., and Mark-Moser, M., 2020, A systematic, science-driven approach for predicting subsurface properties. Interpretation, 8:1, 167-181 https://doi.org/10.1190/INT-2019-0019.1
Cumulative spatial impact layers: A novel multivariate spatio‐temporal analytical summarization tool
Romeo, L., Nelson, J., Wingo, P., Bauer, J., Justman, D., Rose, K. 2019. Cumulative spatial impact layers: A novel multivariate spatio‐temporal analytical summarization tool. Transactions in GIS.00:1–29. https://doi.org/10.1111/tgis.12558
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