AINeutralarXiv – CS AI · 6h ago6/10
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Surrogate models for Rock-Fluid Interaction: A Grid-Size-Invariant Approach
Researchers develop grid-size-invariant neural network surrogate models for predicting rock-fluid interactions in porous media, offering a computationally cheaper alternative to traditional high-fidelity simulations. The approach demonstrates that UNet++ architecture outperforms standard UNet for this application, enabling significant memory reduction during training while maintaining prediction accuracy.