Improving the Signal‐to‐Noise Ratio of Seismological Datasets by Unsupervised Machine Learning-Reference-Cited by-同舟云学术

Improving the Signal‐to‐Noise Ratio of Seismological Datasets by Unsupervised Machine Learning

Published:2019-05-22 Issue: Volume: Page:
ISSN:0895-0695
Container-title:Seismological Research Letters
language:en
Short-container-title:

Author:

Chen Yangkang¹,Zhang Mi²,Bai Min¹,Chen Wei³⁴

Affiliation:

1. School of Earth Sciences, Zhejiang University, Number 866, Yuhangtang Road, Xihu District, Hangzhou 310027, Zhejiang Province, China, yangkang.chen@zju.edu.cn

2. State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, 18 Fuxue Road, Beijing 102200, China, cupmi@sina.com

3. Key Laboratory of Exploration Technology for Oil, and Gas Resources of Ministry of Education, Yangtze University, Number 111, Daxue Road, Caidian District, Wuhan 430100, China, chenwei2014@yangtzeu.edu.cn

4. Also at Hubei Cooperative Innovation Center of Unconventional Oil and Gas, Number 111, Daxue Road, Caidian District, Wuhan 430100, China.

Publisher

Seismological Society of America (SSA)

Subject

Geophysics

Link

https://pubs.geoscienceworld.org/ssa/srl/article-pdf/doi/10.1785/0220190028/4719010/srl-2019028.1.pdf

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