1887

Abstract

Summary

Two ideas are presented in this paper. First, we develop an analytic extension of a time-frequency decomposition, the amplitude of which is a high-resolution time-frequency decomposition that produces very tight energy peaks around the instantaneous frequency and the phase of which is a high precision and structured representation of the frequency content over signal’s entire bandwidth. Second, we build upon this signal representation by developing a Q-factor estimation method that does so by balancing both the amplitude and phase information content of the complex time-frequency decomposition. This estimator uses a propagator based on the Kolsy-Futterman formalism, which has a real part associated with attenuation and an imaginary part associated with dispersion, both of which are Q-dependent. The two methods are matched to take advantage of both amplitude and phase information of the time-frequency distribution. We apply both methods to a synthetic seismic trace and to real marine data. In the synthetic example, instantaneous frequency and Q-factor are determined successfully. The phase of the TFD reveals the instantaneous frequency, with greater sharpness, in both the synthetic and, most markedly, in the marine data.

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/content/papers/10.3997/2214-4609.201413254
2015-06-01
2024-04-18
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References

  1. Boashash, B., Lovell, B., Whitehouse, H.
    , 1987. High-Resolution Time-Frequency Signal Analysis by Parametric Modeling of the Wigner-Ville Distribution, in 1st IASTED International Symposium on Signal Processing and Its Applications: 297–302.
    [Google Scholar]
  2. Futterman, W.I.
    , 1962. Dispersive Body Waves, J. Geophysical Research67, 5279–5291.
    [Google Scholar]
  3. Nunes, B deC. N., Medeiros, W. E., Nascimento, A. doN., Moreira, J.A. deM.
    , 2011. Estimating quality factor from surface seismic data: A comparison of current approaches, Journal of Applied Geophysics75(2), 161–170.
    [Google Scholar]
  4. Porsani, M.J., Ursin, B, Silva, M.G.
    , 2013. Dynamic estimation of reflectivity by minimum-delay seismic trace decomposition, Geophysics78(3), V109–V117.
    [Google Scholar]
  5. Toverud, T., Ursin, B.
    , 2005. Comparison of seismic attenuation models using zero-offset vertical seismic profiling (VSP) data, Geophysics70(2), F17–F25.
    [Google Scholar]
  6. Wang, Y
    , 2008. Seismic inverse Q filtering, Brackwell Publishing.
    [Google Scholar]
  7. , 2014. Stable Q analysis on vertical seismic profiling data, Geophysics79(4), D217–D225.
    [Google Scholar]
  8. Zoukanery, I.M., Porsani, M.J.
    , 2013. High-resolution time-frequency representation of seismic traces using discrete Wigner-Ville distribution combined with the Maximum Entropy Method: Application for attenuation characterization, Extended Abstract in 13th International Congress of the Brazilian Geophysical Society.
    [Google Scholar]
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