Seismic noise attenuation by signal reconstruction: an unsupervised machine learning approach-Reference-Cited by-同舟云学术

Seismic noise attenuation by signal reconstruction: an unsupervised machine learning approach

Published:2021-05-16 Issue:5 Volume:69 Page:984-1002
ISSN:0016-8025
Container-title:Geophysical Prospecting
language:en
Short-container-title:Geophysical Prospecting

Author:

Gao Yang¹²,Zhao Pingqi³,Li Guofa¹²^ORCID,Li Hao¹²

Affiliation:

1. State Key Laboratory of Petroleum Resources and Prospecting, School of Geophysics China University of Petroleum‐Beijing Changping Beijing 102249 China

2. Key Laboratory of Geophysical Exploration of CNPC Changping Beijing 102249 China

3. Dagang Oil field Company PetroChina Tianjin 300280 China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Geochemistry and Petrology,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/1365-2478.13070

Reference55 articles.

1. Lateral prediction for noise attenuation by t-x and f-x techniques

2. Simultaneous dictionary learning and denoising for seismic data

3. Wavelet based seismic signal de-noising using Shannon and Tsallis entropy

4. Random and coherent noise attenuation by empirical mode decomposition

5. Random noise reduction

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