An Intelligent Recognition Method for Low-Grade Fault Based on Attention Mechanism and Encoder–Decoder Network Structure

Low-grade faults play an important role in controlling oil and gas accumulations, but their fault throw is small and difficult to identify. Traditional low-grade fault recognition methods are time-consuming and inaccurate. Therefore, this study proposes a combination of a simulated low-grade fault s...

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Bibliographic Details

Published in:	Energies (Basel) Vol. 15; no. 21; p. 8098
Main Authors:	Zhang, Yujie, Wang, Dongdong, Ding, Renwei, Yang, Jing, Zhao, Lihong, Zhao, Shuo, Cai, Minghao, Han, Tianjiao
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.11.2022
Subjects:	Accuracy Algorithms Analysis Artificial intelligence attention mechanism Deep learning Fault lines low-grade fault Methods Neural networks SE-UNet seismic data interpretation Semantics
ISSN:	1996-1073, 1996-1073
Online Access:	Get full text
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