subsurface fluid flow

Physics-Informed Spatiotemporal Surrogate Modeling and Robust Operational Optimization for CO₂ Applications in Subsurface Flow under Permeability Uncertainty

Zhao Beichen, Visiting Student, Applied Mathematics and Computational Science

Sep 17, 12:00 - 13:00

B9 R2325

Physics-informed Neural Networks Deep learning numerical simulations uncertainty quantification subsurface fluid flow

This talk presents a physics-informed spatiotemporal surrogate that predicts coupled CO₂ storage and geothermal responses under geological uncertainty and enables rapid, risk-aware optimization of staged well controls.