38 citations · 50 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 12 cited
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…
physics.geo-ph2021
Computationally Efficient Multiscale Neural Networks Applied To Fluid Flow In Complex 3D Porous Media
Javier Santos, Ying Yin, Honggeun Jo +6
The permeability of complex porous materials can be obtained via direct flow simulation, which provides the most accurate results, but is very computationally expensive. In particu…
physics.app-ph2020★ 38 cited
Modeling nanoconfinement effects using active learning
Javier E. Santos, Mohammed Mehana, Hao Wu +5
Predicting the spatial configuration of gas molecules in nanopores of shale formations is crucial for fluid flow forecasting and hydrocarbon reserves estimation. The key challenge…