Amplitude-Preserving 3-D TV Regularization for Seismic Random Noise Attenuation

被引：0

作者：

Zhang, Peng ^{[1
]}

Hao, Yaju ^{[1
]}

Li, Hongxing ^{[1
]}

Zhang, Hua ^{[1
]}

Yin, Duowen ^{[1
]}

Ai, Hanbing ^{[2
]}

机构：

[1] East China Univ Technol, Sch Geophys & Measurement Control Technol, Nanchang 330013, Jiangxi, Peoples R China

[2] China Univ Geosci, Sch Geophys & Geomat, Wuhan 430074, Hubei, Peoples R China

来源：

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2025年 / 22卷

基金：

中国国家自然科学基金;

关键词：

Three-dimensional displays; TV; Noise; Noise reduction; Linear programming; Noise measurement; Training; Fourier transforms; Convolution; Inverse problems; 3-D seismic random noise attenuation; amplitude preserving; Lagrange interpolation; second-order difference; total variation (TV) regularization;

D O I：

10.1109/LGRS.2025.3542040

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

Conventional total variation (TV) regularization denoising model is typically constructed by the first-order differences in both lateral and vertical directions. However, first-order differences will result in poor amplitude-preserving outcomes for 3-D seismic random noise attenuation. To address this issue, in this letter, we reform the lateral- and vertical-related constraints in conventional TV regularization function based on high-order differences and Lagrange interpolation to adapt to the lateral and vertical features of seismic data, respectively. Then, we obtain our amplitude-preserving 3-D TV regularization method. In order to optimize the corresponding 3-D denoising objective function, we transform it into frequency-domain and propose a fast optimization method based on the split Bregman algorithm. Both synthetic and field data examples show that our proposed method can yield higher fidelity denoising results compared to the conventional approach.

引用

页数：5

共 17 条

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