ARTICLE

Seismic trace noise removal by smoothed SureShrink

REGIS NUNES VARGAS ANTÔNIO CLÁUDIO PASCIOARELLI VEIGA
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Faculty of Electrical Engineering, Federal University of Uberlândia, Uberlândia, MG, Brazil,
JSE 2020, 29(4), 363–370;
Submitted: 9 June 2025 | Revised: 9 June 2025 | Accepted: 9 June 2025 | Published: 9 June 2025
© 2025 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

Vargas, R.N. and Veiga, A.C.P., 2020. Seismic trace noise removal by smoothed SureShrink. Journal of Seismic Exploration, 29: 363-370. Seismic traces are usually corrupted by Additive White Gaussian Noise (AWGN). AWGN hinders the evaluation of seismic attributes and can lead to distortions during seismic interpretation. Therefore, the development of methods that can effectively remove the noise and extract the signal from the seismic trace is critical. Here we propose a new seismic trace noise removal method called SureShrinkWin, which evaluates the estimates obtained by the SureShrink method when SureShrink is applied in signal windows. To validate the efficacy of the SureShrinkWin method, we performed a Monte Carlo Simulation that considered sixteen seismic traces that were obtained from the astsa R package.

Keywords
wavelets
Monte Carlo simulation
SureShrink
seismic trace
denoising
References
  1. Condat, L., 2013. A direct algorithm for 1D total variation denoising. IEEE Sign.
  2. Process. Lett., 20: 1054-1057.
  3. Damati, A., Daoud, 0. and Hamarsheh, Q., 2016. Enhancing the odd peaks detection in
  4. OFDM systems using wavelet transforms. Internat. J. Communic., Netw. Syst.
  5. Sci, 9: 295-303.
  6. Donoho, D.L. and Johnstone, I.M., 1995. Adapting to unknown smoothness via wavelet
  7. shrinkage. J. Am. Statist. Assoc., 90: 432, 1200-1224.
  8. Gomez, J.L. and Velis, D.R., 2016. 'A simple method inspired by empirical mode
  9. decomposition for denoising seismic data. Geophysics, 81(6): V403-V413.
  10. Han, J. and van der Baan, M., 2015. Microseismic and seismic denoising via ensemble
  11. empirical mode decomposition and adaptive thresholding. Geophysics, 80(6):
  12. KS69-KS80.
  13. Han, G. and Xu, Z., 2016. Electrocardiogram signal denoising based on a new improved
  14. wavelet thresholding. Rev. Sci. Instrum., 87(8): 084303.
  15. Liu, Y., Dang, B., Li, Y., Lin, H. and Ma, H., 2016. Applications of Savitzky-Golay
  16. filter for seismic random noise reduction. Acta Geophys. 64: 101-124.
  17. Meyer, Y., 1993. Wavelets: Algorithms and Applications. Soc. Industr. Appl.
  18. Mathemat, Philadelphia, PA.
  19. Mohanalin, J., Prabavathy, S., Torrents-Barrena, J., Puig, D. and Beena, M., 2016.
  20. A novel wavelet seismic denoising method using type ii fuzzy. Appl. Soft
  21. Comput., 48: $507-S521.
  22. Mooney, CL. 1997. Monte Carlo Simulation. Sage Publications, Vol. 116. Thousand
  23. aks, CA.
  24. Mousavi, S.M. and Langston, C.A., 2016. Hybrid seismic denoising using higher-order
  25. statistics and improved wavelet block thresholding. Bull. Seismol. Soc. Am.,
  26. 106: 1380-1393.
  27. Ning, X. and Selesnick, I.W., 2013. ECG enhancement and QRS detection based on
  28. sparse derivatives. Biomed. Sign. Process. Contr., 8: 713-723.
  29. Percival, D.B. and Walden, A.T., 2006. Wavelet Methods for Time Series Analysis.
  30. Cambridge University Press, Cambridge.
  31. Perrone, D. and Favaro, P., 2016. A clearer picture of total variation blind
  32. deconvolution. IEEE Transact. Patt. Analys. Mach. Intell., 38: 1041-1055.
  33. Stein, C.M., 1981. Estimation of the mean of a multivariate normal distribution. Ann.
  34. Statist., 9: 1135-1151.
  35. Vargas, R.N. and Veiga, A.C.P., 2017. Seismic trace noise reduction by wavelets and
  36. double threshold estimation. IET Signal Process., 1069-1075.
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Journal of Seismic Exploration, Electronic ISSN: 0963-0651 Print ISSN: 0963-0651, Published by AccScience Publishing