Seismic random noise suppression using deep convolutional autoencoder neural network

Due to human or environmental factors, random noise will inevitably be introduced during seismic data acquisition. Contaminated seismic data seriously affect subsequent seismic data processing and imaging. In this paper, we propose a deep convolutional autoencoder neural network for denoising, which...

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Bibliographic Details

Published in:	Journal of applied geophysics Vol. 178; p. 104071
Main Authors:	Song, Hui, Gao, Yang, Chen, Wei, Xue, Ya-juan, Zhang, Hua, Zhang, Xiang
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.07.2020
Subjects:	Deep convolutional autoencoder Noise suppression Seismic data Unsupervised learning Unsupervised learning Seismic data Noise suppression Deep convolutional autoencoder
ISSN:	0926-9851, 1879-1859
Online Access:	Get full text
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