1887

Abstract

Summary

Seismic data is the non-stationary signal, deep reflection signal is weak, and low signal-to-noise ratio, which challenges extracting geological information. We present an adaptive progressive denoising method that enhances the signal-noise ratio of weak signal data. Unlike traditional methods that use a global noise variance, we calculate local noise variances using a Laplacian mask, which adapts to the varying characteristics of seismic data. By leveraging this local variance, we apply a Gaussian bilateral kernel to suppress high-amplitude noise in the time domain and low-amplitude noise in the frequency domain. The method extends to three dimensions by adjusting kernel parameters during iterative updates. Tests field seismic data confirm the method’s effectiveness and adaptability, showing superior performance in improving SNR compared to dictionary learning and optimal damped rank reduction method.

© EAGE Publications BV
Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.202510388
2025-06-02
2026-02-07

  • From This Site

    /content/papers/10.3997/2214-4609.202510388
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. WangX, WenB, and MaJ. [2019]. Denoising with weak signal preservation by group-sparsity transform learning. Geophysics, 84(6): V351–V368.
     [Google Scholar]
  2. LinY., and ZhangJ. [2020]. Progressive denoising of seismic data via robust noise estimation in dual domains. Geophysics, 85(1): V99–V118.
     [Google Scholar]
  3. LiS. [1996]. Robustizing robust M-estimation using deterministic annealing. Pattern Recognition, 29(1): 159–166.
     [Google Scholar]
  4. Chen, Y. [2020]. Fast dictionary learning for noise attenuation of multidimensional seismic data. Geophysical Journal International, 222(3): 1717–1727.
     [Google Scholar]
  5. BaiM., HuangG., WangH., and ChenY. [2020]. Seismic signal enhancement based on the low-rank methods. Geophysical Prospecting, 68(9): 2783–2807.
     [Google Scholar]
  6. WangW., YangJ., QinN., LiZ., HuangJ., and ShanT. [2024]. An Adaptive High-Dimensional Progressive Denoising Method for Seismic Weak Signal Enhancement. IEEE Transactions on Geoscience and Remote Sensing.
     [Google Scholar]
/content/papers/10.3997/2214-4609.202510388
Loading
An Adaptive Progressive Seismic Denoising Method for Enhancing Weak Seismic Signals
Conference Proceedings 2025, 1 (2025); https://doi.org/10.3997/2214-4609.202510388
/content/papers/10.3997/2214-4609.202510388
/content/papers/10.3997/2214-4609.202510388
Loading

Data & Media loading...

Most Cited This Month Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error