1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 1 cited
Accelerated training of deep learning surrogate models for surface displacement and flow, with application to MCMC-based history matching of CO2 storage operations
Yifu Han, Francois P. Hamon, Louis J. Durlofsky
Deep learning surrogate modeling shows great promise for subsurface flow applications, but the training demands can be substantial. Here we introduce a new surrogate modeling frame…
cs.LG2023★ 1 cited
History Matching for Geological Carbon Storage using Data-Space Inversion with Spatio-Temporal Data Parameterization
Su Jiang, Louis J. Durlofsky
History matching based on monitoring data will enable uncertainty reduction, and thus improved aquifer management, in industrial-scale carbon storage operations. In traditional mod…
cs.LG2022
Multi-Asset Closed-Loop Reservoir Management Using Deep Reinforcement Learning
Yusuf Nasir, Louis J. Durlofsky
Closed-loop reservoir management (CLRM), in which history matching and production optimization are performed multiple times over the life of an asset, can provide significant impro…