CO2 Storage Modeling, Analytics, and Risk Reduction Technologies
Closed-Loop Geologic CO₂ Storage Operation for De-Risking and Optimization
This project develops a closed-loop framework for safe and efficient CO2 injection using real-time monitoring and adaptive control. It combines data and deep learning to manage risks like induced seismicity.
Behnam Jafarpour
Roger Ghanem
Birendra Jha
Tieyuan Zhu
Sanjay Srinivasan
Physics-Informed Neural Network for Real-Time Prediction and Intelligent Management of CO2 Injection-Induced Microseismicity
This project develops a physics-informed, data-driven framework to guide CO2 injection using monitoring data, enabling improved seismicity prediction, reduced risks, and enhanced storage safety and efficiency.
Yan Liu
Behnam Jafarpour
Parisa Shokouhi
Derek Elsworth
Coupled Geochemistry and Transport Dynamics of CO2 Leakage: Lab Experiments and Modeling
This project advances understanding of CO2 leakage by integrating laboratory experiments with multiphysics simulations, enabling prediction of geochemical impacts on reservoir and caprock properties and quantification of leakage risks and pathways under field conditions.
Birendra Jha
Felipe de Barros
Anne Menefee
Derek Elsworth
De-Risking Geologic CO2 Storage Permitting and Approval
This project addresses legal and regulatory challenges in geologic CO2 storage (GCS), supporting science-informed frameworks that reduce uncertainty, balance stakeholder interests, and enable scalable project deployment.
Donald Paul
Behnam Jafarpour
Seth Blumsack
Hannah Wiseman
Anne Menefee
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