Rose, R. Rowan, C., Sabbatino, M., Baker, V., Bauer, J., Creason, C.G., Jones, T.J., Justman, D., Romeo, L., Suhag, A., Yeates, D., and Walker, S., submitted, Developing a Virtual Subsurface Data Framework: Transforming DOE’s EDX data lake using ML/NLP, Annual Meeting 2019, Session: IN020 – Data Integration: Enabling the Acceleration of Science Through Connectivity, Collaboration, and Convergent Science. https://agu.confex.com/agu/fm19/meetingapp.cgi/Paper/596761
disCO2ver
Unlocking data-driven capabilities for the entire CCS community
Bibliographies
Developing a Virtual Subsurface Data Framework: Transforming DOE’s EDX data lake using ML/NLP
Moving data “rocks” out of hard places: adapting and innovating data science tools to improve geoscience analytics
Yeates, D., Walker, S., Fillingham, J., Sabbatino, M., Suhag, A., Rose, K., Mark-Moser, M., Creason, C.G., Baker, V., submitted, Moving data “rocks” out of hard places: adapting and innovating data science tools to improve geoscience analytics, AGU Annual Meeting 2019, Session IN005 – AI for Model and Data Integration in the Geosciences. https://ui.adsabs.harvard.edu/abs/2019AGUFMIN32B..09Y/abstract
Subsurface Trend Analysis
Rose, K., Mark-Moser, M., Suhag, A. Subsurface Trend Analysis: A methodical framework for artificial intelligence subsurface property prediction. Machine Learning for Unconventional Resources, Nov. 18th 2019, University of Houston, Texas. https://www.osti.gov/servlets/purl/1778138
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
Putting Data to Work: Transforming Disparate Open-Source Data for Engineered-Natural Systems and Models
Creason, C.G., Romeo, L., Bauer, J., Rose, K., Rowan, C., and Sabbatino, M., 2019, Putting Data to Work: Transforming Disparate Open-Source Data for Engineered-Natural Systems and Models, AGU Annual Meeting 2019, Session: IN020 – Data Integration: Enabling the Acceleration of Science Through Connectivity, Collaboration, and Convergent Science. https://www.osti.gov/biblio/1778210
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
Influence of Effective Stress and Transport on Mechanical and Chemical Alteration Processes at the Cement-Caprock Interface
Rhino, K.; Iyer, J.; Walsh, S. D. C.; Carroll, S. A.; Smith, M. M. Influence of Effective Stress and Transport on Mechanical and Chemical Alteration Processes at the Cement-Caprock Interface. International Journal of Greenhouse Gas Control 2021,109, Article 103340. https://www.sciencedirect.com/science/article/pii/S175058362100092X?via%3Dihub
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
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
Modeling the MT and CSEM Response scCO2 Plume at the Kemper CarbonSAFE Site (FWP-1022403)
Hammack, R. (2021, August 5). Modeling the MT and CSEM Response scCO2 Plume at the Kemper CarbonSAFE Site (FWP-1022403) [Conference presentation]. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Hammack5.pdf
Fostering Data Curation Throughout the Entire Carbon Storage Data Life Cycle via the Energy Data eXchange and GeoCube
Morkner, P., Bauer, J., Rose, K., Rowan, C., Barkhurst, A. (2021, July 27). Fostering Data Curation Throughout the Entire Carbon Storage Data Life Cycle via the Energy Data eXchange and GeoCube. [Conference presentation]. Invited talk at the CCUS Database Virtual Symposium. https://www.osti.gov/servlets/purl/1844394
AI/ML Forecasting of Offshore Platform Integrity to Improve Safety and Reliability
Romeo, L., Dyer, A., Bauer, J., Barkhurst, A., Duran, R., Nelson, J., Sabbatino, M., Wenzlick, M., Wingo, P., Zaengle, D. and Rose, K. 2021. Forecasting Offshore Platform Integrity: Applying Machine Learning Algorithms to Quantify Lifespan and Mitigate Risk. Machine Learning in Oil & Gas. April 15, 2021. Virtual. https://www.osti.gov/servlets/purl/1845120
Forecasting Offshore Platform Integrity: Applying Machine Learning Algorithms to Quantify Lifespan and Mitigate Risk
Romeo, L., Dyer, A., Bauer, J., Barkhurst, A., Duran, R., Nelson, J., Sabbatino, M., Wenzlick, M., Wingo, P., Zaengle, D. and Rose, K. (2021, April 9). Forecasting Offshore Platform Integrity: Applying Machine Learning Algorithms to Quantify Lifespan and Mitigate Risk [Conference presentation]. Machine Learning in Oil & Gas. April 15, 2021. Virtual. https://edx.netl.doe.gov/sites/offshore/forecasting-offshore-platform-integrity-applying-machine-learning-algorithms-to-quantify-lifespan-and-mitigate-risk/
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
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
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
