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Examining Possible CCS Deployment Pathways: Onshore and Offshore (FWP-1022464)

Grant, T. (2021, August 9). Examining Possible CCS Deployment Pathways: Onshore and Offshore. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Grant6.pdf

National Risk Assessment Partnership: NRAP Tools and Recommended Practices for Containment Assurance and Leakage Risk Management

Bacon, D. Pawar, R. (2021, August 9). NRAP Tools and Recommended Practices for Containment Assurance and Leakage Risk Management. [Conference presentation]. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Bacon6.pdf

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

White, J. Templeton, D. (2021, August 9). National Risk Assessment Partnership: NRAP Tools and Recommended Practices for Induced Seismicity [Conference presentation]. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_White6_0.pdf

NRAP Phase II – Managing Risks and Reducing Uncertainties: An Overview of Research Objectives and Accomplishments

Dilmore, R. Gasperikova, E. Thomas, B. (2021, August 6). NRAP Phase II – Managing Risks and Reducing Uncertainties: An Overview of Research Objectives and Accomplishments [Conference presentation]. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Dilmore6.pdf

SMART: Real Time Visualization for Rock and Fluid Properties

Crandall, D. Alumbaugh, D. (2021, August 6). SMART: Real Time Visualization for Rock and Fluid Properties. [Conference presentation]. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Crandall6.pdf

Carbon Storage Data Integration, Visualization, and Application via EDX and GeoCube

Morkner, P. Bauer, J. Rowan, C. Barkhurst, A. Rose, K. (2021). Carbon Storage Data Integration, Visualization, and Application via EDX and Geocube. 2021 Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Morkner6.pdf

SMART: Real Time Visualization for Pressure and Stress

White, J. (2021). SMART: Real Time Visualization of Pressure and Stress. 2021 Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_White6.pdf

Using SmartParse NLP Tools to Develop a Living Database for Carbon Storage Data

Morkner, P. Sabbatino, M. (2021, August 9). Using SmartParse NLP Tools to Develop a Living Database for Carbon Storage Data [Conference presentation]. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Morkner5.pdf

NETL RIC’s Carbon Storage Research Supporting Field Efforts (FWP-1022403)

Crandall, D.  (2021, August 5). NETL RIC’s Carbon Storage Research Supporting Field Efforts (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_Crandall5.pdf

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

Regulatory Considerations for Geologic Storage of Carbonated Brine Streams. 16th International Conference on Greenhouse Gas Control Technologies

Van Voorhees, R.; Thomas, R. B.; Schwartz, B.; Dilmore, R.; Hamling, J.; Klapperich, R.; Taunton, M. Regulatory Considerations for Geologic Storage of Carbonated Brine Streams. 16th International Conference on Greenhouse Gas Control Technologies, GHGT-16, 23-24th October 2022, Lyon, France. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4285028

Enhancing High-Fidelity Nonlinear Solver with Reduced Order Model

Kadeethum, T., O’Malley, D., Ballarin, F., Ang, I., Fuhg, J.N., Bouklas, N., Silva, V.L.S., Salinas, P., Heaney, C.E., Pain, C.C., Lee, S., Viswanathan, H.S., and Yoon, H., “Enhancing High-Fidelity Nonlinear Solver with Reduced Order Model,” Scientific Reports, 12, Article 20229. (2022) https://doi.org/10.1038/s41598-022-22407-6.

A Quantitative Comparison of Risk-based Leak Mitigation Strategies at a Geologic Carbon Storage Site

Lackey, G.; Mitchell, N.; Schwartz, B.; Liu, G.; Vasylkivska, V. S.; Strazisar, B.; Dilmore, R. M. A Quantitative Comparison of Risk-based Leak Mitigation Strategies at a Geologic Carbon Storage Site. 16th International Conference on Greenhouse Gas Control Technologies, GHGT-16, 23-24th October 2022, Lyon, France. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4271578

Continuous Conditional Generative Adversarial Networks for Data-Driven Solutions of Poroelasticity with Heterogeneous Material Properties

Kadeethum, T., O’Malley, D., Choi, Y., Viswanathan, H.S., Bouklas, N., and Yoon, H., “Continuous Conditional Generative Adversarial Networks for Data-Driven Solutions of Poroelasticity with Heterogeneous Material Properties,” Computers & Geosciences, Vol. 167, 105212, (2022), https://doi.org/10.1016/j.cageo.2022.105212.

TOUGH3-FLAC3D: a modeling approach for parallel computing of fluid flow and geomechanics

Rinaldi, A. P.; Rutqvist, J.; Luu, K.; Blanco-Martin, L.; Hu, M. et al. TOUGH3-FLAC3D: a modeling approach for parallel computing of fluid flow and geomechanics. Computational Geosciences 2022, 26, 1563–1580. https://doi.org/10.1007/s10596-022-10176-0.

Data-driven offshore CO2 saline storage assessment methodology

Romeo, L., Thomas, R., Mark-Moser, M., Bean, A., Bauer, J. and Rose, K., 2022. Data-driven offshore CO2 saline storage assessment methodology. International Journal of Greenhouse Gas Control, 119, p.103736. https://www.sciencedirect.com/science/article/pii/S1750583622001542

Data-driven offshore CO2 saline storage assessment methodology

Romeo, L., Thomas, R., Mark-Moser, M., Bean, A., Bauer, J. and Rose, K., 2022. Data-driven offshore CO2 saline storage assessment methodology. International Journal of Greenhouse Gas Control, 119, p.103736. https://www.sciencedirect.com/science/article/pii/S1750583622001542

3D Visualization of Integrated Geologic and Geophysical Subsurface Data Using Open-Source Programming: A Case Study Using Data from the MSEEL Project

Panetta, B., Carr, T., and Fathi, E., “3D Visualization of Integrated Geologic and Geophysical Subsurface Data Using Open-Source Programming: A Case Study Using Data from the MSEEL Project,” AAPG and SEG Second International Meeting for Applied Geoscience & Energy, August 14-15, 2022, Houston, TX, expanded abstract, https://doi.org/10.1190/image2022-3746025.1

Deep Learning Multiphysics Network for Imaging CO2 Saturation and Estimating Uncertainty in Geological Carbon Storage

Um, E.S., Alumbaugh, D., Commer, M., Feng, S., Gasperikova, E., Li, Y., Lin, Y., and Samarasinghe, S., “Deep Learning Multiphysics Network for Imaging CO2 Saturation and Estimating Uncertainty in Geological Carbon Storage;” Geophysical Prospecting, (2022) https://doi.org/10.1111/1365-2478.13257.

Multi-Level of Fracture Network Imaging: A HFTS Use Case and Knowledge Transferring

Liu, G., Kumar, A., Zhao, S., Shih, C., Vasylkivska, V., Holcomb, P., Hammack, R., Ilconich, J., and Bromhal, G., “Multi-Level of Fracture Network Imaging: A HFTS Use Case and Knowledge Transferring,” presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, Houston, Texas, USA, (June 2022) https://doi.org/10.15530/urtec-2022-3723466.

Possible Controls on Porosity Preservation in the Andaman Forearc Gas Hydrate System

Johnson, J., Rose, K., Torres, M. (2020, Jan). Possible controls on porosity preservation in the Andaman forearc gas hydrate system: OSR, AOM, and/or marine silicate weathering [Conference presentation]. Geologic Society of America Meeting 2020, Session: T99. Records of Early Diagenesis in Modern and Ancient Sediments. https://community.geosociety.org/gsa2020/program/technical

Back to the Future: Rescue, Curation, and Transformation of a Corpus of Carbon Storage Data

Sabbatino, M., Baker, V., Bauer, J., Creason, C., Romeo, L., Rose, K., Rowan, C., Zoch, G., submitted, Back to the Future: Rescue, Curation, and Transformation of a Corpus of Carbon Storage Data, Annual Meeting 2019, Session: AGU Dirty Stories of Data Rescue. https://www.osti.gov/servlets/purl/1778129

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 

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

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