Articles | Volume 15, issue 17
https://doi.org/10.5194/gmd-15-6841-2022
https://doi.org/10.5194/gmd-15-6841-2022
Development and technical paper
 | 
08 Sep 2022
Development and technical paper |  | 08 Sep 2022

DeepISMNet: three-dimensional implicit structural modeling with convolutional neural network

Zhengfa Bi, Xinming Wu, Zhaoliang Li, Dekuan Chang, and Xueshan Yong

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Latest update: 28 Mar 2024
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Short summary
We present an implicit modeling method based on deep learning to produce a geologically valid and structurally compatible model from unevenly sampled structural data. Trained with automatically generated synthetic data with realistic features, our network can efficiently model geological structures without the need to solve large systems of mathematical equations, opening new opportunities for further leveraging deep learning to improve modeling capacity in many Earth science applications.