Porous structure reconstruction using convolutional neural networks

DOI10.1007/S11004-018-9743-0zbMath1402.86005OpenAlexW2804870822WikidataQ129827935 ScholiaQ129827935MaRDI QIDQ1622858

Christoph H. Arns, Ji-Youn Arns, Sheik S. Rahman, Yu-Zhu Wang

Publication date: 21 November 2018

Published in: Mathematical Geosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11004-018-9743-0

zbMATH Keywords

convolutional neural network\(\mu\)-CTporous structure reconstruction

Mathematics Subject Classification ID

Computational methods for problems pertaining to geophysics (86-08) Neural nets and related approaches to inference from stochastic processes (62M45)

Related Items (8)

Hierarchical reconstruction of 3D well-connected porous media from 2D exemplars using statistics-informed neural network ⋮ Geological facies recovery based on weighted \(\ell_1\)-regularization ⋮ Statistical characterization and reconstruction of heterogeneous microstructures using deep neural network ⋮ An end-to-end three-dimensional reconstruction framework of porous media from a single two-dimensional image based on deep learning ⋮ Reconstruction, optimization, and design of heterogeneous materials and media: basic principles, computational algorithms, and applications ⋮ Stochastic reconstruction of 3D microstructures from 2D cross-sectional images using machine learning-based characterization ⋮ A deep-learning-based geological parameterization for history matching complex models ⋮ Numerical modelling of reservoir at pore scale: a comprehensive review

Uses Software

• ImageNet
• AlexNet
• DnCNN

Cites Work

• Robust Single Image Super-Resolution via Deep Networks With Sparse Prior
• Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
• MODELLING A FOOD MICROSTRUCTURE BY RANDOM SETS
• Flow in simulated porous media

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