Improving Seismic Fault Recognition with Self-Supervised Pre-Training: A Study of 3D Transformer-Based with Multi-Scale Decoding and Fusion

Seismic fault interpretation holds great significance in the fields of geophysics and geology. However, conventional methods of seismic fault recognition encounter various issues. For example, models trained on synthetic data often exhibit inadequate generalization when applied to field seismic data...

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Bibliographic Details

Published in:	Remote Sensing
Main Authors:	Zeren Zhang, Ran Chen, Jinwen Ma
Format:	Article
Language:	English
Published:	MDPI AG 2024-03-01
Subjects:	seismic faults detection 3D segmentation self-supervised pre-training
Online Access:	https://www.mdpi.com/2072-4292/16/5/922