3 papers
cs.LG2026
Learning Pore-scale Multiphase Flow from 4D Velocimetry
Chunyang Wang, Linqi Zhu, Yuxuan Gu +9
Multiphase flow in porous media underpins subsurface energy and environmental technologies, including geological CO storage and underground hydrogen storage, yet pore-scale dyn…
cs.LG2023
Learning CO plume migration in faulted reservoirs with Graph Neural Networks
Xin Ju, François P. Hamon, Gege Wen +3
Deep-learning-based surrogate models provide an efficient complement to numerical simulations for subsurface flow problems such as CO geological storage. Accurately capturing t…
cs.LG2021
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…