Articles | Volume 16, issue 9
https://doi.org/10.5194/gmd-16-2495-2023
https://doi.org/10.5194/gmd-16-2495-2023
Development and technical paper
 | 
09 May 2023
Development and technical paper |  | 09 May 2023

ClinoformNet-1.0: stratigraphic forward modeling and deep learning for seismic clinoform delineation

Hui Gao, Xinming Wu, Jinyu Zhang, Xiaoming Sun, and Zhengfa Bi

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Latest update: 28 May 2024
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Short summary
We propose a workflow to automatically generate synthetic seismic data and corresponding stratigraphic labels (e.g., clinoform facies, relative geologic time, and synchronous horizons) by geological and geophysical forward modeling. Trained with only synthetic datasets, our network works well to accurately and efficiently predict clinoform facies in 2D and 3D field seismic data. Such a workflow can be easily extended for other geological and geophysical scenarios in the future.