A Deep-Learning-Based Geological Parameterization for History Matching Complex Models

7 Jul 2018 Yimin Liu Wenyue Sun Louis J. Durlofsky

A new low-dimensional parameterization based on principal component analysis (PCA) and convolutional neural networks (CNN) is developed to represent complex geological models. The CNN-PCA method is inspired by recent developments in computer vision using deep learning... (read more)

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METHOD TYPE
PCA
Dimensionality Reduction