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ML Clustering to Identify Natural Gas Pipeline Infrastructure Vulnerabilities

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

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

Estimating Carbon Storage Resources in Offshore Geologic Environments

Cameron, E.; Thomas, R.; Bauer, J.; Bean, A.; DiGiulio, J.; Disenhof, C.; Galer, S.; Jones, K.; Mark-Moser, M.; Miller, R.; Romeo, L.; Rose, K. Estimating Carbon Storage Resources in Offshore Geologic Environments; NETL-TRS-14-2018; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Albany, OR, 2018; p 32. DOI: 10.18141/1464460 https://edx.netl.doe.gov/dataset/estimating-carbon-storage-resources-in-offshore-geologic-environments  

Variable Grid Method: An Intuitive Approach for Simultaneously Quantifying and Visualizing Spatial Data and Uncertainty

Bauer, J. R., and Rose, K., 2015, Variable Grid Method: an Intuitive Approach for Simultaneously Quantifying and Visualizing Spatial Data and Uncertainty, Transactions in GIS. 19(3), p. 377-397. https://doi.org/10.1111/tgis.12158

Machine Learning Application for CCUS Carbon Storage: Fracture Analysis and Mapping in The Illinois Basin

Liu, G., Kumar, A., Harbert, W., Siriwardane, H., Myshakin, E., Crandall, D., Cunha, L., (2024, June 23). Machine Learning Application for CCUS Carbon Storage: Fracture Analysis and Mapping in The Illinois Basin [Conference presentation], ARMA 24–1183, 58th U.S. Rock Mechanics/Geomechanics Symposium, Golden, Colorado. https://www.osti.gov/biblio/2228745

Supporting Safe CO2 Transport-Route Planning: A Multifaceted Geospatial Database Enhancing Carbon Models

 Schooley, C., Houghton, B., Romeo, L., Gao, M., Leveckis, S., Justman, D., Chong, L.,Sharma, M., Bauer, J., and Rose, K., “Supporting Safe CO2 Transport-Route Planning: A Multifaceted Geospatial Database Enhancing Carbon Models,” SAMI Technical Talk, San Diego, CA, June 20, 2024.

Advanced Offshore Hazard Forecasting to Enable Resilient Offshore Operations

Mark-Moser, M. K., Romeo, L., Duran, R., Bauer, J., Rose, K., (2024, May 6). Advanced Offshore Hazard Forecasting to Enable Resilient Offshore Operations. [Conference presentation] Offshore Technology Conference 2024. Houston, TX.  https://www.osti.gov/biblio/2352616

EDX disCO2ver, Fostering Public-Private Partnerships for Accelerated Advancements in AI for Energy

Rose, K., 2024, “EDX disCO2ver, Fostering Public-Private Partnerships for Accelerated Advancements in AI for Energy”, AI in Oil & Gas Conference, April 9-10, 2024. Invited.

Web-Based GIS Data: Observation of Differences in Performance and Management

Pramuk, J., McFarland, D., Chittum, J., Bauer, J., and Rose, K., “Web-Based GIS Data: Observation of Differences in Performance and Management,” Esri Developer Summit, Palm Springs, CA, March 12–15, 2024.

Carbon Storage Technical Viability Approach and National Data Assessment

Mark-Moser, M., Creason, C.G., Mulhern, J., Shay, J., Lara, A., and Rose, K., “Carbon Storage Technical Viability Approach and National Data Assessment,” presented at the CCUS 2024 SPE AAPG SEG, Houston, TX, March 11–13, 2024.

Developing a National Oil & Gas Wellbore Database and Visualization Tool to Support Locating and Characterizing Undocumented Wells

Bauer, J., Romeo, L., Sharma, M., Amrine, D., Pfander, I., Sabbatino, M., and Rose, K., “Developing a National Oil & Gas Wellbore Database and Visualization Tool to Support Locating and Characterizing Undocumented Wells,” American Geophysical Union (AGU) Fall Meeting 2023, San Francisco, CA, December 11–15, 2023.

Multi-Factor Assessment for Decarbonization via Technically Viable Carbon Storage

Mark-Moser, M., Creason, C.G., Mulhern, J.S., Shay, J., and Rose, K., “Multi-Factor Assessment for Decarbonization via Technically Viable Carbon Storage,” American Geophysical Union (AGU) Fall Meeting 2023, San Francisco, CA, December 11–15, 2023.

The DisCO2ver Platform: Curating Data and Tools for Geologic Carbon Sequestration and Deep Subsurface Systems Research

Morkner, P., Rose, K., Rowan, C., Jones, TJ., McFarland, D., Maurice, A., Baker, V., and Bauer, J., “The DisCO2ver Platform: Curating Data and Tools for Geologic Carbon Sequestration and Deep Subsurface Systems Research,” American Geophysical Union (AGU) Fall Meeting 2023, San Francisco, CA, December 11–15, 2023.

An Accessible and Interoperable CO2 Transport Routing Geodatabase for Scalable Computing & Decision Support

Schooley, C., Romeo, L., Pfander, I., Justman, D., Sharma, M., Bauer, J., and Rose, K., “An Accessible and Interoperable CO2 Transport Routing Geodatabase for Scalable Computing & Decision Support,” American Geophysical Union (AGU) Fall Meeting 2023, San Francisco, CA, December 11–15, 2023.

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