Seismic Random Noise Attenuation Using a Tied-Weights Autoencoder Neural Network

Seismic Random Noise Attenuation Using a Tied-Weights Autoencoder Neural Network

Random noise is unavoidable in seismic data acquisition due to anthropogenic impacts or environmental influences. Therefore, random noise suppression is a fundamental procedure in seismic signal processing. Herein, a deep denoising convolutional autoencoder network based on self-supervised learning...

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Bibliographic Details
Main Authors: Huailai Zhou, Yangqin Guo, Ke Guo
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Minerals
Subjects:
autoencoder convolutional neural network
noise suppression
seismic data
tied weights
self-supervised learning
Online Access:https://www.mdpi.com/2075-163X/11/10/1089

Internet

https://www.mdpi.com/2075-163X/11/10/1089

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