Mesh generation and optimization from digital rock fractures based on neural style transfer

Mesh generation and optimization from digital rock fractures based on neural style transfer

The complex geometric features of subsurface fractures at different scales makes mesh generation challenging and/or expensive. In this paper, we make use of neural style transfer (NST), a machine learning technique, to generate mesh from rock fracture images. In this new approach, we use digital roc...

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Bibliographic Details
Main Authors: Mengsu Hu, Jonny Rutqvist, Carl I. Steefel
Format: Article
Language:English
Published: Elsevier 2021-08-01
Series:Journal of Rock Mechanics and Geotechnical Engineering
Subjects:
Convolutional neural network (CNN)
Neural style transfer (NST)
Digital rock
Discrete fractures
Discontinuum asperities
Grain aggregates
Online Access:http://www.sciencedirect.com/science/article/pii/S1674775521000500

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http://www.sciencedirect.com/science/article/pii/S1674775521000500

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