AI RESEARCH
Convolutional Surrogate for 3D Discrete Fracture-Matrix Tensor Upscaling
arXiv CS.LG
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ArXi:2604.02335v1 Announce Type: new Modeling groundwater flow in three-dimensional fractured crystalline media requires accounting for strong spatial heterogeneity induced by fractures. Fine-scale discrete fracture-matrix (DFM) simulations can capture this complexity but are computationally expensive, especially when repeated evaluations are needed. To address this, we aim to employ a multilevel Monte Carlo (MLMC) framework in which numerical homogenization is used to upscale sub-resolution fracture effects when transitioning between accuracy levels.