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Developing a Virtual Subsurface Data Framework: Transforming DOE’s EDX data lake using ML/NLP

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

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

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.

NRAP-Open-IAM: Generic Aquifer Component Development and Testing

Bacon, D. H. NRAP-Open-IAM: Generic Aquifer Component Development and Testing. PNNL-32590, 2022, Pacific Northwest National Laboratory, Richland, WA. https://doi.org/10.2172/1845855.

Machine Learning Enhanced Seismic Monitoring at 100 km and 10 m Scales

Chai, C., Maceira, M., and EGS Collab Team, “Machine Learning Enhanced Seismic Monitoring at 100 km and 10 m Scales,” in Proceedings, 47th Workshop on Geothermal Reservoir Engineering, edited, Stanford University, Stanford, California, 47, 635–645, (2022) https://www.osti.gov/biblio/1845768.

Sensitivity of geophysical techniques for monitoring secondary CO2 storage plumes

Gasperikova, E.; Appriou, D.; Bonneville, A.; Feng, Z.; Huang, L.; Gao, K.; Yang, X.; Daley, T. Sensitivity of geophysical techniques for monitoring secondary CO2 storage plumes. International Journal of Greenhouse Gas Control 2022, 114, Article 103585. https://doi.org/10.1016/j.ijggc.2022.103585.

Scaling Behavior of Thermally Driven Fractures in Deep Low-Permeability Formations: A Plane Strain Model with 1-D Heat Conduction

Chen, B.; Zhou, Q. Scaling Behavior of Thermally Driven Fractures in Deep Low-Permeability Formations: A Plane Strain Model with 1-D Heat Conduction. Journal of Geophysical Research – Solid Earth 2022, Research Article. https://doi.org/10.1029/2021JB022964.

Distilling Data to Drive Carbon Storage Insights

Morkner, P.; Bauer, J.; Creason, C.; Sabbatino, M.; Wingo, P.; Greenburg, R.; Walker, S.; Yeates, D.; Rose, K. Distilling Data to Drive Carbon Storage Insights. Computers & Geosciences 2022, 158, Article 104945. https://doi.org/10.1016/j.cageo.2021.104945.

Deep Learning Inversion of Gravity Data for Detection of CO2 Plumes in Overlying Aquifers

Yang, X.; Chen, X.; Smith, M.M. Deep Learning Inversion of Gravity Data for Detection of CO2 Plumes in Overlying Aquifers. Journal of Applied Geophysics 2022, 196(104507). https://doi.org/10.1016/j.jappgeo.2021.104507.

A Review of Well Integrity Based on Field Experience at Carbon Utilization and Storage Sites

Iyer, J.; Lackey, G.; Edvardsen, L.; Bean, A.; Carroll, S.A.; Huerta, N.; Smith, M.M.; Torsaeter, M.; Dilmore, R.M.; Cerasi, P. A Review of Well Integrity Based on Field Experience at Carbon Utilization and Storage Sites. International Journal of Greenhouse Gas Control 2022, 113(103533). https://doi.org/10.1016/j.ijggc.2021.103533

A Review of Well Integrity Based on Field Experience at Carbon Utilization and Storage Sites

Iyer, J.; Lackey, G.; Edvardsen, L.; Bean, A.; Carroll, S.A.; Huerta, N.; Smith, M.M.; Torsaeter, M.; Dilmore, R.M.; Cerasi, P. A Review of Well Integrity Based on Field Experience at Carbon Utilization and Storage Sites. International Journal of Greenhouse Gas Control 2022, 113(103533). https://doi.org/10.1016/j.ijggc.2021.103533

Impact of time-dependent deformation on geomechanical risk for geologic carbon storage

Bao T.; Burghardt, J. A.; Gupta, V.; White, M. D. Impact of time-dependent deformation on geomechanical risk for geologic carbon storage. International Journal of Rock Mechanics and Mining Sciences 2021, 148, 104940. PNNL-SA-161528. https://doi.org/10.1016/j.ijrmms.2021.104940.

Carbon Storage Technical Viability Approach

Mark-Moser, M. Creason, C. Mulhern, J. Shay, J. Lara, A. Rose, K. (2023, August 28). Carbon Storage Technical Viability Approach [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS28_Mark-Moser.pdf

EDX Utilization of Cloud Open Data Programs to Enhance Reuse of Large CS Datasets

Rowan, C. Rose, K. (2023, August 28). EDX Utilization of Cloud Open Data Programs to Enhance Reuse of Large CS Datasets. FECM/NETL Carbon Management Meeting 2023 [Conference presentation].  https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS28_Rowan.pdf

Novel Geomechanical Signal Methodologies (FWP-1022403)

Hakala, A. (2021, August 6). Novel Geomechanical Signal Methodologies. [Conference presentation]. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Hakala6.pdf

SMART: Real Time Forecasting for Carbon Storage

McGuire, T. Yonkofski, C. (2021). SMART: Real Time Forecasting of Carbon Storage. 2021 Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_McGuire6.pdf

SMART Task 3: Pressure and Stress

White, J. Williams-Stroud, M. (2022). SMART Phase III: Pressure and Stress. 2022 Carbon Management Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/22CM_CTS18_White_2.pdf

Real Time Visualization of Rock and Fluid Properties

Alumbaugh, D. (2022). Real Time Visualization of Rock and Fluid Properties. 2022 Carbon Management Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/22CM_CTS18_Alumbaugh.pdf

SMART: Overview of SMART Initiative – Phase I Accomplishments and Phase II Plans

Bromhal, G. Mishra, S. (2022). SMART: Overview of SMART Initiative – Phase I Accomplishments and Phase II Introduction. 2022 Carbon Management Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/22CM_CTS18_Bromhal.pdf

NETL RIC CarbonSAFE Assistance (FWP-1022403)

Crandall, D. (2022). NETL RIC CarbonSAFE Assistance. 2022 Carbon Management Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/22CM_CTS18_Crandall.pdf

National Risk Assessment Partnership: Maturing Tools and Recommended Practices for Site and Basin-Scale Risk Management

Bacon, D. (2022). NRAP: Tools and Recommended Practices for Site and Basin Scale Risk Management. 2022 Carbon Management Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/22CM_CTS18_Bacon.pdf

National Risk Assessment Partnership: Tools and Recommended Practices for Induced Seismicity Risk Management

White, J. (2022). NRAP: Tools and Recommended Practices for Induced Seismicity and Risk Management. 2022 Carbon Management Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/22CM_CTS18_White.pdf

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