Automatic high-resolution microseismic event detection via supervised machine learning-Reference-Cited by-同舟云学术

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Automatic high-resolution microseismic event detection via supervised machine learning

Published:2019-06-11 Issue:3 Volume:218 Page:2106-2121
ISSN:0956-540X
Container-title:Geophysical Journal International
language:en
Short-container-title:

Author:

Qu Shan¹,Guan Zhe²^ORCID,Verschuur Eric¹,Chen Yangkang³

Affiliation:

1. Delft university of technology, Departments of Imaging Physics, Mekelweg 2, 2628 CD Delft, Netherlands

2. Rice University, Applied Physics Program, Houston, TX, USA

3. School of Earth Sciences, Zhejiang University, Hangzhou, Zhejiang Province 310027, China

Publisher

Oxford University Press (OUP)

Subject

Geochemistry and Petrology,Geophysics

Link

http://academic.oup.com/gji/advance-article-pdf/doi/10.1093/gji/ggz273/28794877/ggz273.pdf

Reference94 articles.

1. A robust neural network-based approach for microseismic event detection;Akram,2017

2. Automatic phase pickers: their present use and future prospects;Allen;Bull. seism. Soc. Am.,1982

3. Automatic earthquake recognition and timing from single traces;Allen;Bull. seism. Soc. Am.,1978

4. A technique for identifying microseismic multiplets and application to the valhall field, north seaidentifying microseismic multiplets;Arrowsmith;Geophysics,2006

5. Seismic deconvolution using iteartive transform-domain sparse inversion;Bai;J. Seism. Explor.,2018

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