1 citations · 4 across the 4 of their papers we have counts for
4 papers
Multimodal Auto-regressive Transformer Surrogate for Modeling Variable Operations and Quantifying Uncertainty in Geological Carbon Storage
Yifu Han, Louis J. Durlofsky
The use of variable well perforation and injection strategies can improve the efficiency of geological carbon storage operations. We develop a new multimodal auto-regressive transf…
Recurrent Transformer U-Net Surrogate for Flow Modeling and Data Assimilation in Subsurface Formations with Faults
Yifu Han, Louis J. Durlofsky
Many subsurface formations, including some of those under consideration for large-scale geological carbon storage, include extensive faults that can strongly impact fluid flow. In…
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…
Surrogate Model for Geological CO2 Storage and Its Use in Hierarchical MCMC History Matching
Yifu Han, Francois P. Hamon, Su Jiang +1
Deep-learning-based surrogate models show great promise for use in geological carbon storage operations. In this work we target an important application - the history matching of s…