AI RESEARCH
Enhancing the Parameterization of Reservoir Properties for Data Assimilation Using Deep VAE-GAN
arXiv CS.LG
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ArXi:2603.18766v1 Announce Type: new Currently, the methods called Iterative Ensemble Smoothers, especially the method called Ensemble Smoother with Multiple Data Assimilation (ESMDA) can be considered state-of-the-art for history matching in petroleum reservoir simulation. However, this approach has two important limitations: the use of an ensemble with finite size to represent the distributions and the Gaussian assumption in parameter and data uncertainties. This latter is particularly important because many reservoir properties have non-Gaussian distributions.