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Optimal wavelet filter for suppression of coherent noise with an application to seismic data

Author

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  • Leite, F.E.A.
  • Montagne, Raúl
  • Corso, G.
  • Vasconcelos, G.L.
  • Lucena, L.S.

Abstract

Wavelet analysis is combined with the Karhunen–Loève (KL) transform into an innovative hybrid method for locally filtering coherent noise. In applying our method, the original time series is first decomposed with wavelet transform, the scales more contaminated with noise are reduced by an attenuation factor Af, and the signal is reconstructed using the inverse wavelet transform. Then the KL transform is applied to the reconstructed signal and the behavior of the first energy modes is analyzed as a function of Af. The point corresponding to a minimum in the first mode is identified with the maximum extraction of the coherent noise. Our methodology is applied with success to seismic data with the aim of locally extracting the relevant coherent noise, namely the ground roll noise. The procedure can be easily extended to other situations where an undesirable signal is associated with a specific set of energy modes.

Suggested Citation

  • Leite, F.E.A. & Montagne, Raúl & Corso, G. & Vasconcelos, G.L. & Lucena, L.S., 2008. "Optimal wavelet filter for suppression of coherent noise with an application to seismic data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(7), pages 1439-1445.
  • Handle: RePEc:eee:phsmap:v:387:y:2008:i:7:p:1439-1445
    DOI: 10.1016/j.physa.2007.08.062
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    References listed on IDEAS

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    1. Corso, G. & Kuhn, P.S. & Lucena, L.S. & Thomé, Z.D., 2003. "Seismic ground roll time–frequency filtering using the gaussian wavelet transform," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 318(3), pages 551-561.
    2. Montagne, Raúl & Vasconcelos, Giovani L., 2006. "Extremum criteria for optimal suppression of coherent noise in seismic data using the Karhunen–Loève transform," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(1), pages 122-125.
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    Cited by:

    1. Oliveira, M.S. & Henriques, M.V.C. & Leite, F.E.A. & Corso, G. & Lucena, L.S., 2012. "Seismic denoising using curvelet analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(5), pages 2106-2110.

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