11 citations · 22 across the 4 of their papers we have counts for
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cs.LG2021★ 2 cited
Deep-learning-based coupled flow-geomechanics surrogate model for CO sequestration
Meng Tang, Xin Ju, Louis J. Durlofsky
A deep-learning-based surrogate model capable of predicting flow and geomechanical responses in CO2 storage operations is presented and applied. The 3D recurrent R-U-Net model comb…
physics.geo-ph2021★ 9 cited
A Deep Learning-Accelerated Data Assimilation and Forecasting Workflow for Commercial-Scale Geologic Carbon Storage
Hewei Tang, Pengcheng Fu, Christopher S. Sherman +6
Fast assimilation of monitoring data to update forecasts of pressure buildup and carbon dioxide (CO2) plume migration under geologic uncertainties is a challenging problem in geolo…