13 citations · 20 across the 8 of their papers we have counts for
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cs.LG2024
Likelihood-Free Inference and Hierarchical Data Assimilation for Geological Carbon Storage
Wenchao Teng, Louis J. Durlofsky
Data assimilation will be essential for the management and expansion of geological carbon storage operations. In traditional data assimilation approaches a fixed set of geological…
cs.CE2024
Graph Network Surrogate Model for Optimizing the Placement of Horizontal Injection Wells for CO2 Storage
Haoyu Tang, Louis J. Durlofsky
Optimizing the locations of multiple CO2 injection wells will be essential as we proceed from demonstration-scale to large-scale carbon storage operations. Well placement optimizat…
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…