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Noise reduction for desert seismic data using spectral kurtosis adaptive bandpass filter

  • Haitao Ma
  • Zebin Qian
  • Yue Li
  • Hongbo Lin
  • Dan Shao
  • Baojun Yang
Review Article - Applied Geophysics
  • 23 Downloads

Abstract

In view of the heterogeneity and week similarity of random noise in the desert seismic exploration, and lots of random noise focused on low frequency, the traditional bandpass filter and wavelet transform are used to separate the signal and noise. Although there are some denoising effects, the noise cannot be suppressed well, and effective signal is damaged to some extent. Because of the above shortcomings, we propose a bandpass filter denoising method based on spectral kurtosis in this paper. This method is based on the signal and the random noise’s energy distribution characteristics in the frequency domain. First, through short-time Fourier transform (STFT), the spectral kurtosis of noisy signals is obtained. Second, we design a new threshold by the obtained spectral kurtosis, the value of spectral kurtosis greater than the threshold is preserved, and the spectral kurtosis less than the threshold is set to 0. So, the method realises the adaptive choice of the filter passband, getting an adaptive bandpass filter. At the same time, the noise can be suppressed to a greater extent while the effective signal is retained very well. The noise removal results of synthetic data and actual data show that the proposed method has very good denoising performance and amplitude preserving capability.

Keyword

Desert noise Spectral kurtosis STFT Bandpass filter 

Notes

Acknowledgements

The work was supported by The Nation Science Foundation of China (Grant Nos. 41730422, 41774117).

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Copyright information

© Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2018

Authors and Affiliations

  • Haitao Ma
    • 1
  • Zebin Qian
    • 1
  • Yue Li
    • 1
  • Hongbo Lin
    • 1
  • Dan Shao
    • 1
  • Baojun Yang
    • 1
  1. 1.College of Communication EngineeringJilin UniversityChangchunChina

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