Seismic Random Noise Attenuation via Low-Rank Tensor Network

Seismic Random Noise Attenuation via Low-Rank Tensor Network

Seismic data are easily contaminated by random noise, impairing subsequent geological interpretation tasks. Existing denoising methods like low-rank approximation (LRA) and deep learning (DL) show promising denoising capabilities but still have limitations; for instance, LRA performance is parameter...

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Bibliographic Details
Main Authors: Taiyin Zhao, Luoxiao Ouyang, Tian Chen
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
Subjects:
low-rank approximation (LRA)
deep learning (DL)
total variation (TV)
weighted tensor nuclear norm (WTNN)
random noise
Online Access:https://www.mdpi.com/2076-3417/15/7/3453
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