Automatic 3D fault segmentation based on multi-scale feature fusion model with compound loss function
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s12145-024-01319-1.pdf
Reference66 articles.
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2. Alfarhan M, Deriche M, Maalej A (2022) Robust Concurrent Detection of Salt Domes and Faults in Seismic Surveys Using an Improved UNet Architecture. IEEE Access 10:39424–39435. https://doi.org/10.1109/ACCESS.2020.3043973
3. AlSalmi H, Elsheikh AH (2024) Automated seismic semantic segmentation using attention U-Net. GEOPHYSICS 89:WA247–WA263. https://doi.org/10.1190/geo2023-0149.1
4. Bemmel PPV, Pepper REF (2000) Seismic signal processing method and apparatus for generating a cube of variance values. U.S. Patent No. 6,151,555
5. Chang D, Yong X, Yang W, Wang Y, Guo TC (2019) U_Net & residual neural networks for seismic fault interpretation. European Association of Geoscientists & Engineers 2019(1):1–5. https://doi.org/10.3997/2214-4609.201901387
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