23 citations · 60 across the 15 of their papers we have counts for
3 papers · 1 filter
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…
Machine Learning in Heterogeneous Porous Materials
Marta D'Elia, Hang Deng, Cedric Fraces +21
The "Workshop on Machine learning in heterogeneous porous materials" brought together international scientific communities of applied mathematics, porous media, and material scienc…
MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework
Chiyu Max Jiang, Soheil Esmaeilzadeh, Kamyar Azizzadenesheli +6
We propose MeshfreeFlowNet, a novel deep learning-based super-resolution framework to generate continuous (grid-free) spatio-temporal solutions from the low-resolution inputs. Whil…