1887

Abstract

Summary

The local singularity of signal often carries a great deal of important information. Unlike Fourier transform, the wavelet transform has good local property in time and frequency domains, and it is suitable for analyzing the non-stationary signal. A new wavelet basis named impedance basis is proposed on the basis of the properties of impedance data in the paper, which can indicate discontinuity of impedance data in time. The wavelet transform based on impedance basis can effectively extract the information about impedance interfaces. The analysis for Marmousi impedance model and real seismic impedance data shows that the presented approach is applicable to detection of impedance interfaces. In addition, it is also beneficial to identification and interpretation of thin-bed.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.20140865
2014-06-16
2020-04-09
Loading full text...

Full text loading...

References

  1. Daubechies
    . [1990] The wavelet transform time-frequency localization and signal analysis. IEEE Trans on Information Theory, 36, 961–1005.
    [Google Scholar]
  2. Rioul, O., Vetterti. M.
    [1991] Wavelets and Signal Processing. IEEE transactions on SP Mag, 11, 14–38.
    [Google Scholar]
  3. Jiang, Q., Goh, S.S., Lin, Z.
    [1999] Local discriminate time-frequency atoms for signal classification. Signal Processing, 72, 47–52.
    [Google Scholar]
  4. Mallat, S., Hwang, W. L.
    [1992] Singularity detection and procession with wavelets. IEEE Trans. on Information Theory, 38, 617–643.
    [Google Scholar]
  5. Lner
    Lneret al. [2004] SPICE: A new general seismic attribute. 74th Annual International Meeting, SEG, Expanded Abstracts, 433–436.
    [Google Scholar]
  6. Mallat, S.
    [1985] A Theory for Multiresolution Signal Decomposition. The Wavelet Representation IEEE transactions on PAML, 11, 674–693.
    [Google Scholar]
  7. [1989] Multi-resolution approximations and wavelet orthogonal bases of L2(R). IEEE transactions on Math, 315, 67–87.
    [Google Scholar]
  8. Mallat, S., Zhong, S.
    [1992] Characterization of Signals from Multi-scale Edges. IEEE Trans on Pattern Analysis and Machine Intelligence, 14, 710–732.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.20140865
Loading
/content/papers/10.3997/2214-4609.20140865
Loading

Data & Media loading...

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