1887
Volume 41, Issue 9
  • ISSN: 0263-5046
  • E-ISSN: 1365-2397

Abstract

Abstract

Matching pursuit is a well-known algorithm that enables the decomposition of seismic signal with high temporal and frequency resolutions by adaptively extracting wavelets that locally match the signal. However, this method processes each trace independently and does not take into consideration the lateral continuity of the seismic data. In addition, this approach is very sensitive to subtle changes in the seismic signals leading to non-unique solutions. Furthermore, matching pursuit suffers from performance limitations. In this article, a new method is proposed in which geological lateral continuity is captured using a Relative Geological Time (RGT) model. This technique is a RGT-based multichannel matching pursuit which consists of extracting wavelets using the classical matching pursuit method and laterally propagating the extracted wavelets by following their respective RGT age. The method has been applied to the MAUI dataset, offshore New-Zealand. The results indicate that this method improves the lateral continuity while still respecting the geology. The computing time required to extract the iso-frequencies is tremendously lessened, and the extracted iso-frequencies are less sensitive to random noise.

EAGE Publications BV
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2023-09-01
2026-02-16

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References

  1. Allen, J.B. [1977]. Short term spectral analysis, synthesis, and modification by discrete Fourier transform.IEEE Transactions on Acoustics, Speech, and Signal Processing, 25, 235–238.
     [Google Scholar]
  2. Castagna, J.P. and Sun, S. [2006]. Comparison of spectral decomposition methods.First Break, 24(3), 75–79.
     [Google Scholar]
  3. Chopra, S. and Marfurt, K.J. [2007]. Seismic Attributes for Prospect Identification and Reservoir Characterization. Society of Exploration Geophysicists.
     [Google Scholar]
  4. Daubechies, I. [1992]. Ten Lectures on Wavelets. Regional Conference Series in Applied Mathematics, SIAM, ISBN 978-0-89871-274-2.
     [Google Scholar]
  5. Durot, B., Mangue, M., Luquet, B., Adam, J. and Daynac, N. [2017]. Innovative and Interactive Methods Emphasizing Geological Events through Spectral Decomposition New Zealand Case Study.79th EAGE Conference & Exhibition, Extended Abstract, 1–5.
     [Google Scholar]
  6. Li, Y., Wang, J., Li, H. and Ren, P. [2020]. Peak colocalized orthogonal matching pursuit for seismic trace decomposition.IEEE Access, 8, 8620–8626.
     [Google Scholar]
  7. Liu, L., Wu, Y., Han, D. and Li, X. [2004]. Time-Frequency decomposition based on Ricker wavelet.SEG Technical Program Expanded Abstracts, 1937–1940.
     [Google Scholar]
  8. Mallat, G. and Zhang, Z. [1993]. Matching pursuits with time frequency dictionaries.IEEE Trans, Signal Processing, 41, 3397–3415.
     [Google Scholar]
  9. Partyka, G., Gridley, J. and Lopez, J. [1999]. Interpretational applications of spectral decomposition in reservoir characterization.The Leading Edge, 18, 353–360.
     [Google Scholar]
  10. Pauget, F., Lacaze, S. and Valding, T. [2009]. A global approach to seismic interpretation base on cost function and minimization.SEG Technical Program Expanded Abstracts, 2592–2596.
     [Google Scholar]
  11. Satish, K.S., Routh, P. S., Anno, P.D. and Castagna, J.P. [2003]. Time-frequency attribute of seismic data using continuous wavelet transform.SEG Technical Program Expanded Abstracts, 1481–1484.
     [Google Scholar]
  12. Wang, S., Wang, Y., Chen, Y., Liu, X. and Yang, B. [2016]. A high-resolution processing technique for improving the energy of weak signal based on matching pursuit.Annals of Geophysics, 59(2), S0209.
     [Google Scholar]
  13. Wang, Y. [2010]. Multichannel matching pursuit for seismic trace decomposition.Geophysics, 75, V61–66.
     [Google Scholar]
  14. Xu, L., Yin, X. and Li, K. [2020]. Enhancing the resolution of time-frequency spectrum using directional multichannel matching pursuit.Acta Geophysica, 68, 1643–1652.
     [Google Scholar]
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RGT-Based Multi-Channel Matching Pursuit: a Fast and Stable Spectral Decomposition Method
First Break 41, 61 (2023); https://doi.org/10.3997/1365-2397.fb2023074
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  • Article Type: Research Article

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