1887
Volume 68, Issue 2
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

The widely used wavelets in the context of the matching pursuit are mostly focused on the time–frequency attributes of seismic traces. We propose a new type of wavelet basis based on the classic Ricker wavelet, where the quality factor is introduced. We develop a new scheme for seismic trace decomposition by applying the multi‐channel orthogonal matching pursuit based on the proposed wavelet basis. Compared with the decomposition by the Ricker wavelets, the proposed method could use fewer wavelets to represent the seismic signal with fewer iterations. Besides, the quality factor of the subsurface media could be extracted from the decomposition results, and the seismic attenuation could be compensated expediently. We test the availability of the proposed methods on both synthetic seismic record and field post‐stack data.

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/content/journals/10.1111/1365-2478.12846
2019-09-17
2024-04-19
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References

  1. BoydS. and VandenbergheL.2004. Convex Optimization. Cambridge University Press.
    [Google Scholar]
  2. ChakrabortyA. and OkayaD.1995. Frequency‐time decomposition of seismic data using wavelet‐based methods. Geophysics60, 1906–1916.
    [Google Scholar]
  3. CohenL.1995. Time‐Frequency Analysis. Prentice Hall, Inc.
    [Google Scholar]
  4. DonohoD.L., TsaigY., DroriI. and StarckJ.L.2006. Sparse solution of underdetermined linear equations by stagewise orthogonal matching pursuit. IEEE Transactions on Information Theory58, 1094–1121.
    [Google Scholar]
  5. DongW.1999. AVO detectability against tuning and stretching artifacts. Geophysics64, 494–503.
    [Google Scholar]
  6. DroujinineA.2006. Theory and seismic applications of the eigenimage discrete wavelet transform. Geophysical Prospecting54, 441–461.
    [Google Scholar]
  7. FengX., ZhangX., LiuC. and LuQ.2017. Single‐channel and multi‐channel orthogonal matching pursuit for seismic trace decomposition. Journal of Geophysics and Engineering14, 90–99.
    [Google Scholar]
  8. FomelS.2007. Shaping regularization in geophysical‐estimation problems. Geophysics72, R29–R36.
    [Google Scholar]
  9. GanleyD.C. and KanasewichE.R.1980. Measurement of absorption and dispersion from check shot surveys. Journal of Geophysical Research Solid Earth85, 5219–5226.
    [Google Scholar]
  10. HerrmannF.J., WangD., HennenfentG. and MoghaddamP.P.2008. Curvelet‐based seismic data processing: a multiscale and nonlinear approach. Geophysics73, A1–A5.
    [Google Scholar]
  11. KlugmanS.A., PanjerH.H. and WillmotG.E.2002. Interpolation and Smoothing. John Wiley & Sons, Inc.
    [Google Scholar]
  12. KjartanssonE.1979. Constant Q‐wave propagation and attenuation. Journal of Geophysical Research: Solid Earth84, 4737–4748.
    [Google Scholar]
  13. LongbottomJ., WaldenA.T. and WhiteR.E.1988. Principles and application of maximum kurtosis phase estimation. Geophysical Prospecting36, 115–138.
    [Google Scholar]
  14. LiQ.2017. High‐Resolution Seismic Exploration. Society of Exploration Geophysicists, Houston, TX.
    [Google Scholar]
  15. LiaoQ. and McMechanG.A.1997. Tomographic imaging of velocity and Q, with application to crosswell seismic data from the Gypsy Pilot Site, Oklahoma. Geophysics62, 1804–1811.
    [Google Scholar]
  16. LiuG.C., ChenX.H., DuJ., and LiuY.2011a. Seismic Q estimation using S‐transform with regularized inversion. Oil Geophysical Prospecting46, 417–422.
    [Google Scholar]
  17. LiuG., FomelS. and ChenX.2011b. Time‐frequency analysis of seismic data using local attributes. Geophysics76, P23–P34.
    [Google Scholar]
  18. LiuJ., WuY., HanD. and LiX.2004. Time‐frequency decomposition based on Ricker wavelet. 74th Annual International Meeting, SEG, Expanded Abstracts, 1937–1940.
  19. LiuY. and FomelS.2013. Seismic data analysis using local time‐frequency decomposition. Geophysical Prospecting61, 516–525.
    [Google Scholar]
  20. MallatS.2008. A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way. Academic Press.
    [Google Scholar]
  21. MallatS. and ZhangZ.1993. Matching pursuits with time‐frequency dictionaries. IEEE Transactions on Signal Processing41, 3397–3415.
    [Google Scholar]
  22. MargraveG.F., LamoureuxM.P., GrossmanJ.P. and IliescuV.2002. Gabor deconvolution of seismic data for source waveform and Q correction. 72nd Annual International Meeting, SEG, Expanded Abstracts, 2190–2193.
  23. MargraveG.F., LamoureuxM.P. and HenleyD.C.2011. Gabor deconvolution: estimating reflectivity by nonstationary deconvolution of seismic data. Geophysics76, W15‐W30.
    [Google Scholar]
  24. PatiY.C., RezaiifarR. and KrishnaprasadP.S.1993. Orthogonal matching pursuit: Recursive function approximation with applications to wavelet decomposition. 27th Asilomar Conference on Signals, Systems and Computers, Expanded Abstracts, 40–44. IEEE.
  25. PeterT.2013. Generalized Prony method. PhD thesis, University of Göttingen, Göttingen, Germany.
  26. PinnegarC.R. and MansinhaL.2003. The S‐transform with windows of arbitrary and varying shape. Geophysics68, 381–385.
    [Google Scholar]
  27. PronyR.1795. Essai expérimental et analytique. Annuaire de l' École Poly‐technique1, 24–76.
    [Google Scholar]
  28. RickerN.1953. The form and laws of propagation of seismic wavelets. Geophysics18, 10–40.
    [Google Scholar]
  29. SadeghiM., Babaie‐ZadehM. and JuttenC.2014. Learning overcomplete dictionaries based on atom‐by‐atom updating. IEEE Transactions on Signal Processing62, 883–891.
    [Google Scholar]
  30. SinhaS., RouthP. and AnnoP.2009. Instantaneous spectral attributes using scales in continuous‐wavelet transform. Geophysics74, WA137–WA142.
    [Google Scholar]
  31. StockwellR.G., MansinhaL. and LoweR.P.1996. Localization of the complex spectrum: the S transform. IEEE Transactions on Signal Processing44, 998–1001.
    [Google Scholar]
  32. TroppJ.A. and GilbertA.C.2007. Signal recovery from random measurements via orthogonal matching pursuit. IEEE Transactions on Information Theory53, 4655–4666.
    [Google Scholar]
  33. WangY.2006. Inverse Q ‐filter for seismic resolution enhancement. Geophysics71, V51–V60.
    [Google Scholar]
  34. WangY.2007. Seismic time‐frequency spectral decomposition by matching pursuit. Geophysics72, V13–V20.
    [Google Scholar]
  35. WangY.2008. Seismic Inverse Q Filtering. Blackwell Pub.
    [Google Scholar]
  36. WangY.2010. Multichannel matching pursuit for seismic trace decomposition. Geophysics75, V61–V66.
    [Google Scholar]
  37. WangY.2015. Frequencies of the Ricker wavelet. Geophysics80, A31–A37.
    [Google Scholar]
  38. WhiteR.E.1992. The accuracy of estimating Q from seismic data. Geophysics57, 1508–1511.
    [Google Scholar]
  39. ZhangF. and LiC.2012. Orthogonal time‐frequency atom based fast matching pursuit for seismic signal. Chinese Journal of Geophysics55, 277–283.
    [Google Scholar]
  40. ZhangX., FengX., LiuC., ChenC., LiX. and ZhangY.2017. Seismic matching pursuit decomposition based on the attenuated Ricker wavelet dictionary. 79th EAGE Conference and Exhibition 2017 – Workshops, Extended abstract. Eage.
  41. ZhangX., NilotE., FengX., RenQ. and ZhangZ.2018. Imf‐slices for GPR data processing using variational mode decomposition method. Remote Sensing10, 476.
    [Google Scholar]
  42. ZhaoT. and SongW.2012. An application of matching pursuit time‐frequency decomposition method using multi‐wavelet dictionaries. Petroleum Science9, 310–316.
    [Google Scholar]
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