AI hybrid network accelerates subsurface flow simulations

Researchers have developed a novel hybrid framework that integrates machine learning with multiscale numerical methods to efficiently solve Darcy equations in complex subsurface flow simulations. The approach uses an attention-enhanced neural network to predict multiscale basis functions, significantly accelerating the offline computation stage of the mixed generalized multiscale finite element method (mixed GMsFEM). This learning-based acceleration, combined with a two-grid preconditioned solver for the global system, maintains accuracy and stability even in heterogeneous media with high-contrast coefficients, outperforming existing learning-based methods. AI

IMPACT Accelerates complex simulations, potentially enabling higher-resolution subsurface analysis for fields like geology and reservoir engineering.

RANK_REASON This is a research paper detailing a new computational method. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

• Attention-enhanced Hybrid Network
• Darcy equations
• mixed generalized multiscale finite element method (mixed GMsFEM)
• two-grid preconditioner

• paper
• other

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