Templeton, D., Schoenball, M., Layland-Bachmann, C., Foxall, W., Kroll, K., Burghardt, J., Dilmore, R., White, J.. Recommended Practices for Managing Induced Seismicity Risk Associated with Geologic Carbon Storage (Draft Report) 2021. NRAP Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV. https://www.osti.gov/biblio/1834402/
disCO2ver
Unlocking data-driven capabilities for the entire CCS community
Bibliographies
Recommended Practices for Managing Induced Seismicity Risk Associated with Geologic Carbon Storage
Field-scale fault reactivation experiments by fluid injection highlight aseismic leakage in caprock analogs: Implications for CO2 sequestration
Guglielmi, Y.; Nussbaum, C.; Cappa, F.; de Barros, L.; Rutqvist, J., Birkholzer, J. Field-scale fault reactivation experiments by fluid injection highlight aseismic leakage in caprock analogs: Implications for CO2 sequestration. International Journal of Greenhouse Gas Control 2021, 111, Article 103471. https://doi.org/10.1016/j.ijggc.2021.103471
Experimental workflow to estimate model parameters for evaluating long term viscoelastic response of CO2 storage caprock
Bao, T.; Burghardt, J. A.; Gupta, V.; Edelman, E.; McPherson, B. J.; White, M. D. Experimental workflow to estimate model parameters for evaluating long term viscoelastic response of CO2 storage caprock. International Journal of Rock Mechanics and Mining Sciences, 2021. 146, Article 104796. PNNL-SA-153774. doi:10.1016/j.ijrmms.2021.104796. https://www.sciencedirect.com/science/article/abs/pii/S1365160921001817?via%3Dihub
Alteration of Fractured Foamed Cement Exposed to CO2-Saturated Water: Implications for Well Integrity
Min, Y.; Montross, S.; Spaulding, R.; Brandi, M.; Huerta, N.; Thomas, R.; Kutchko, B. Alteration of Fractured Foamed Cement Exposed to CO2-Saturated Water: Implications for Well Integrity. Environmental Science & Technology 2021, 55(19), 13244-13253. https://doi.org/10.1021/acs.est.1c02699.
NRAP-open-IAM: A flexible open-source integrated-assessment-model for geologic carbon storage risk assessment and management
Vasykivska, V.; Dilmore, R.; Lackey, G.; Zhang, Y.; King, S.; Bacon, D.; Chen, B.; Mansoor, K.;Harp, D. NRAP-open-IAM: A flexible open-source integrated-assessment-model for geologic carbon storage risk assessment and management. Environmental Modeling & Software 2021, 143, Article 105114. https://www.sciencedirect.com/science/article/abs/pii/S1364815221001572?via%3Dihub
Forecasting 3D Structural Complexity with AI/ML method: Mississippi Canyon, Gulf of Mexico
Pantaleone, S., Mark Moser, M., Bean, A., Walker, S., Rose, K., 2021, “Forecasting 3D Structural Complexity with AI/ML method: Mississippi Canyon, Gulf of Mexico”. AAPG/SEG IMAGE conference, Denver, Colorado, September 26, 2021 October 1, 2021. https://edx.netl.doe.gov/sites/offshore/forecasting-3d-structural-complexity-with-ai-ml-method-mississippi-canyon-gulf-of-mexico/
Propagation, arrest, and reactivation of thermally driven fractures in an unconfined half-space using stability analysis
Chen, B.; Zhou, Q. Propagation, arrest, and reactivation of thermally driven fractures in an unconfined half-space using stability analysis. Theoretical and Applied Fracture Mechanics 2021, 114, Article 102969. https://doi.org/10.1016/j.tafmec.2021.102969.
NRAP-Open-IAM: FutureGen2 Component Models
Bacon D. H. NRAP-Open-IAM: FutureGen2 Component Models, 2021. PNNL-31781. Richland, WA: Pacific Northwest National Laboratory. https://www.pnnl.gov/main/publications/external/technical_reports/PNNL-31781.pdf
Assessing Current & Future Infrastructure Hazards: Forecasting Integrity using Machine Learning & Advanced Analytics
Romeo, L. (2021, August 9). Assessing Current & Future Infrastructure Hazards: Forecasting Integrity using Machine Learning & Advanced Analytics [Conference presentation]. Carbon Management and Oil and Gas Research Project Review Meeting. https://netl.doe.gov/sites/default/files/netl-file/20VPRONG_26_Romeo.pdf
NETL’s SmartSearch Deep Learning Tool
Baker, V., Bauer, J., Morkner, P., Rose, K. NETL’s SmartSearch Deep Learning Tool – Scalable data search and parse for carbon storage data discovery. Carbon Management and Oil and Gas Research Project Review Meeting – Carbon Storage. August 9th, 2021. https://netl.doe.gov/sites/default/files/netl-file/21CMOG_CS_Baker9.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.
Advanced Machine Learning and Computational Methods
Schuetter, J. Tartakovsky, A. Shih, C. (2023, August 31). Advanced Machine Learning and Computational Methods [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS31_Schuetter.pdf
Overview of SMART Initiative
Siriwardane H. Mishra, S. (2023, August 31). Overview of SMART Initiative [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS31_Siriwardane.pdf
Assessing Risks of Rapid Commercial-Scale Deployment of Geologic Carbon Storage
Bacon, D. Camargo, J. Kirol, A. Haagenson, R. Creason, C. Lackey, G. Morkner, P. Zhou, Q. Cihan, A. Eier, J. Schmidt, B. (2023, August 31). Assessing Risks of Rapid Commercial-Scale Deployment of Geologic Carbon Storage [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS31_Bacon1.pdf
Developing a Tool to Quantify Liability of Geologic Carbon Storage
Morgan, D. Bello, K. Burghardt, J. Creason, C. Dilmore, R. Gasperikova, E. Grant, T. Huerta, N. Liu, G. Kroll, K. Mark-Moser, M. Oldenburg, C. Rasouli, P. Smith, M. Strazisar, B. Vasylkivska, V. Vikara, D. Warner, T. Wilson, K. (2023, August 31). Developing a Tool to Quantify Liability of Geologic Carbon Storage [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS31_Morgan.pdf
Adaptive, Risk-Based Monitoring of Geologic Carbon Storage
Gasperikova, E. Vasylkivska, V. Yang, X. Huang, L. Hanna, A. Chen, B. Creasy, N. Li, D. Blatter, D. Kumar, A. Dilmore, R. Harbert, B. Morgan, D. Iyer, J.K. Smith, M. Kirol, A. Appriou, D. (2023, August 31). Adaptive, Risk-Based Monitoring of Geologic Carbon Storage [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS31_Gasperikova.pdf
NRAP Phase III Overview: Objectives and Progress
Dilmore, R. (2023, August 31). NRAP Phase III Overview: Objectives and Progress [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS31_Dilmore.pdf
Anonymizing Sensitive Carbon Storage Data Tool
Morkner, P. Bauer, J. Wingo, P. Gao, M. Sharma, M. Hoover, B. Neumann, C. Johnson, C. Schuetter, J. Rose, K. (2023, August 29). Anonymizing Sensitive Carbon Storage Data Tool [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS29_Morkner.pdf
A Comprehensive Dashboard for CS Planning
Justman D. Pantaleone, S. Sharma, M. Romeo, L. Morkner, P. Bauer, J. (2023, August 29). A Comprehensive Dashboard for CS Planning [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS29_Justman.pdf
EDX Cloud Optimization for Carbon Management
Rose, K. Baker, V. (2023, August 28). EDX Cloud Optimization for Carbon Management [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS28_Rose.pdf
Licensing and Virtualizing Carbon Storage Models and Tools via EDX disCO2ver
Zaengle, D. Sinclair, J. Wingo, P. Rowan, C. Rose, K. (2023, August 28). Licensing and Virtualizing Carbon Storage Models and Tools via EDX disCO2ver [Conference presentation]. FECM/NETL Carbon Management Meeting 2023. https://netl.doe.gov/sites/default/files/netl-file/23CM_CTS28_Zaengle.pdf
