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
disCO2ver
Unlocking data-driven capabilities for the entire CTS community
Bibliographies
ML Clustering to Identify Natural Gas Pipeline Infrastructure Vulnerabilities
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
CO2-Locate (v2): A Living National Well Database
Romeo, L., Bauer, J., Pfander, I., Cleaveland, C., Dyer, A., Sabbatino, M., Tetteh, D., and K. Rose. CO2-Locate (v2): A Living National Well Database. 2024 FECM / NETL Carbon Management Research Project Review Meeting. Pittsburgh, PA. August 5–9, 2024.
EDX disCO2ver, Increasing Carbon Transport & Storage Product Awareness and Understanding Through Stakeholder Engagement
Rose, K., 2024, “EDX disCO2ver, Increasing Carbon Transport & Storage Product Awareness and Understanding Through Stakeholder Engagement”, FECM / NETL Carbon Management Research Project Review Meeting. Pittsburgh, PA. August 5-9, 2024.
Developing the Carbon Storage Site Mapping Inquiry Tool (MapIT)
Schooley, C., Pantaleone, S., Shay, J., Strazisar, B., and Morkner, P. “Developing the Carbon Storage Site Mapping Inquiry Tool (MapIT)”. FECM/NETL Carbon Management Meeting. Pittsburgh, PA. August 5-9, 2024.
Dynamic CCS-Energy Community Database and Web Application – What’s New
Sharma, M., Bocan, J., White, C., Malay, C., Cleaveland, C., Rose, K., and Bauer, J., “Dynamic CCS-Energy Community Database and Web Application – What’s New,” FECM/NETL Carbon Management Research Project Review Meeting, Pittsburgh, PA, August 5–9, 2024.
Community Sentiment Analysis with focus on CCS
White, C., Sharma, M., Rose, K., and Bauer, J. “Community Sentiment Analysis with focus on CCS”. 2024 FECM / NETL Carbon Management Research Project Review Meeting. Pittsburgh, PA. August 4-9, 2024.
Deploying a Publicly Available and Living National Oil and Gas Well Geodatabase
Pfander, I., Romeo, L., Amrine, D., Sabbatino, M., Sharma, M., Tetteh, D., and Bauer, J., “Deploying a Publicly Available and Living National Oil and Gas Well Geodatabase,” 2024 Esri User Conference, San Diego, CA, July 15–19, 2024.
A Geodatabase Designed to Inform and Support Safe CO2 Transport-Route Planning
Schooley, C., Romeo, L., Pfander, I., Justman, D., Sharma, M., Bauer, J., and Rose, K.,“A Geodatabase Designed to Inform and Support Safe CO2 Transport-Route Planning,” 2024 Esri User Conference, San Diego, CA. July 15–19, 2024. https://www.osti.gov/biblio/2403249
A Dashboard to Support Community Transitions for Carbon Capture and Storage
Sharma, M., White, C., Cleaveland, C., Amrine, D., Rose, K., and Bauer, J., “A Dashboard to Support Community Transitions for Carbon Capture and Storage,” 2024 Esri User Conference, San Diego, CA, July 15–19, 2024. https://www.osti.gov/biblio/2404263
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,” FECM/NETL Carbon Management Research Project Review Meeting, Pittsburgh, PA, August 5–9, 2024. https://netl.doe.gov/sites/default/files/netl-file/24CM/24CM_CTS3_5_Creason.pdf
Energy Community Dynamic Database for CCS Systems
Sharma, M., White, C., Bocan, J., Cleaveland, C., Malay, C., Bauer, J., and Rose, K., “Energy Community Dynamic Database for CCS Systems,” GES Tech Talk, Morgantown, WV, June 2024.