Seismic fault detection using an encoder–decoder convolutional neural network with a small training set-Reference-Cited by-同舟云学术

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Seismic fault detection using an encoder–decoder convolutional neural network with a small training set

Published:2019-02-01 Issue:1 Volume:16 Page:175-189
ISSN:1742-2132
Container-title:Journal of Geophysics and Engineering
language:en
Short-container-title:

Author:

Li Shengrong¹²³^ORCID,Yang Changchun¹²,Sun Hui¹²³,Zhang Hao¹²

Affiliation:

1. Key Laboratory of Petroleum Resources Research, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China

2. Institutions of Earth Science, Chinese Academy of Sciences, Beijing 100029, China

3. University of Chinese Academy of Sciences, Beijing 100049, China

Funder

Chinese Academy of Sciences

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Management, Monitoring, Policy and Law,Industrial and Manufacturing Engineering,Geology,Geophysics

Link

http://academic.oup.com/jge/article-pdf/16/1/175/28296590/gxy015.pdf

Reference50 articles.

1. TensorFlow: a system for large-scale machine learning;Abadi;et al,2016

2. Improved fault segmentation using a dip guided and modified 3D Sobel filter;Aqrawi,2011

3. Automated fault detection without seismic processing;Araya-Polo;The Leading Edge,2017

4. Segnet: a deep convolutional encoder–decoder architecture for image segmentation;Badrinarayanan;arXiv:1511.00561,2015

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