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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 7

Complementary blind spot strategy and U-shaped Transformer for seismic data denoising

Gao Leia,b,c
Xu Xuana
Luo Xinruia
Min Fana,b,c
a. School of Computer Science & Software Engineering, b. Institute for Artificial Intelligence, c. Lab of Machine Learning, Southwest Petroleum University, Chengdu 610500, China
DOI: 10.19734/j.issn.1001-3695.2024.12.0516

Abstract

Random noise denoising can effectively improves the signal-to-noise ratio (SNR) of seismic data. Blind spot-driven unsupervised denoising methods do not require labelled data and can automatically extract features, but they ignore noise correlations, leading to suboptimal performance. To address this issue, we propose the Complementary Blind Spot Strategy and U-shaped Transformer Seismic Denoising Framework (CBUTS) . First, the complementary blind-spot strategy, which uses trace masking and random masking for complementary sampling to effectively weaken the spatial connections of noise. Secondly, visible blind spot loss function integrates denoised results from both non-blind and blind spots, reducing information loss. Finally, the Transformer-based U-shaped blind spot network (STU-Net) enhances the capture of global and local features, further weakens the noise correlations, and more accurately predicts valid signals. Experimental results show that, compared to classical and advanced supervised and unsupervised methods, CBUTS achieves better performance in denoising noise and preserving the continuity of seismic events. Analysis and comparison confirm the applicability of the method to seismic data denoising.

Foundation Support

南充市-西南石油大学市校科技战略合作专项资金(23XNSYSX0084)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.12.0516
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 7

Publish History

[2025-03-14] Accepted Paper

Cite This Article

高磊, 许轩, 罗芯汭, 等. 互补盲点策略和U型Transformer的地震数据去噪 [J]. 计算机应用研究, 2025, 42 (7). (2025-03-14). https://doi.org/10.19734/j.issn.1001-3695.2024.12.0516. (Gao Lei, Xu Xuan, Luo Xinrui, et al. Complementary blind spot strategy and U-shaped Transformer for seismic data denoising [J]. Application Research of Computers, 2025, 42 (7). (2025-03-14). https://doi.org/10.19734/j.issn.1001-3695.2024.12.0516. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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