A recurrent residual U-Net surrogate predicts dynamic subsurface pressure and saturation maps accurately enough to accelerate history matching in channelized reservoirs by orders of magnitude.
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A deep-learning-based surrogate model for data assimilation in dynamic subsurface flow problems
A recurrent residual U-Net surrogate predicts dynamic subsurface pressure and saturation maps accurately enough to accelerate history matching in channelized reservoirs by orders of magnitude.