most citedDeep-learning-based upscaling method for geologic models via theory-guided convolutional neural network

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

physics.geo-ph2024

Physics-Informed Convolutional Decoder (PICD): A novel approach for direct inversion of heterogeneous subsurface flow

Nanzhe Wang, Xiang-Zhao Kong, Dongxiao Zhang

In this study, we present the development and application of the physics-informed convolutional decoder (PICD) framework for inverse modeling of heterogenous groundwater flow. PICD…

cs.LG2021★ 2 cited

Deep-learning-based upscaling method for geologic models via theory-guided convolutional neural network

Nanzhe Wang, Qinzhuo Liao, Haibin Chang +1

Large-scale or high-resolution geologic models usually comprise a huge number of grid blocks, which can be computationally demanding and time-consuming to solve with numerical simu…