A graph-based Wasserstein autoencoder with a geodesic realism loss can perform history matching across two channelized geological scenarios in a shared latent space.
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History Matching under Uncertainty of Geological Scenarios with Implicit Geological Realism Control with Generative Deep Learning and Graph Convolutions
A graph-based Wasserstein autoencoder with a geodesic realism loss can perform history matching across two channelized geological scenarios in a shared latent space.