1887
  1. Home
  2. A-Z Publications
  3. Geophysical Prospecting
  4. Volume 49, Issue 3
  5. Article
Volume 49, Issue 3
  • E-ISSN: 1365-2478

Abstract

The spiking deconvolution of a field seismic trace requires that the seismic wavelet on the trace be minimum phase. On a dynamite trace, the component wavelets due to the effects of recording instruments, coupling, attenuation, ghosts, reverberations and other types of multiple reflection are minimum phase. The seismic wavelet is the convolution of the component wavelets. As a result, the seismic wavelet on a dynamite trace is minimum phase and thus can be removed by spiking deconvolution. However, on a correlated vibroseis trace, the seismic wavelet is the convolution of the zero‐phase Klauder wavelet with the component minimum‐phase wavelets. Thus the seismic wavelet occurring on a correlated vibroseis trace does not meet the minimum‐phase requirement necessary for spiking deconvolution, and the final result of deconvolution is less than optimal. Over the years, this problem has been investigated and various methods of correction have been introduced. In essence, the existing methods of vibroseis deconvolution make use of a correction that converts (on the correlated trace) the Klauder wavelet into its minimum‐phase counterpart. The seismic wavelet, which is the convolution of the minimum‐phase counterpart with the component minimum‐phase wavelets, is then removed by spiking deconvolution. This means that spiking deconvolution removes both the constructed minimum‐phase Klauder counterpart and the component minimum‐phase wavelets. Here, a new method is proposed: instead of being converted to minimum phase, the Klauder wavelet is removed directly. The spiking deconvolution can then proceed unimpeded as in the case of a dynamite record. These results also hold for gap predictive deconvolution because gap deconvolution is a special case of spiking deconvolution in which the deconvolved trace is smoothed by the front part of the minimum‐phase wavelet that was removed.

Loading

Article metrics loading...

/content/journals/10.1046/j.1365-2478.2001.00260.x
2001-12-21
2024-04-25

  • From This Site

    /content/journals/10.1046/j.1365-2478.2001.00260.x
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. BerkhoutA.J.1984.Seismic Resolution. Elsevier Science Publishing Co.
    [Google Scholar]
  2. BickelS.H.1982. The effect of noise on minimum‐phase vibroseis deconvolution. Geophysics47, 1174–1184.
    [Google Scholar]
  3. CamboisG.2000. Zero‐phasing the zero‐phase source. Leading Edge19, 72–75.
    [Google Scholar]
  4. CarliniA. & StorerP.1991. Seismic vibrator data processing for stratigraphic interpretation: a combined deterministic–statistical approach. First Break9, 458–466.
    [Google Scholar]
  5. FordW.T.1978. Optimum mixed delay spiking filters. Geophysics43, 125–132.
    [Google Scholar]
  6. FuttermanW.I.1962. Dispersive body waves. Journal of Geophysical Research67, 5279–5291.
    [Google Scholar]
  7. GeyerR.1989.Vibroseis. Geophysics Reprint Series, Society of Exploration Geophysicists, Tulsa.
    [Google Scholar]
  8. GibsonB. & LarnerK.1984. Predictive deconvolution and the zero phase source. Geophysics49, 379–397.
    [Google Scholar]
  9. KelamisP.G. & ChiburisE.F.1988. Post‐critical wavelet estimation and deconvolution. Geophysical Prospecting36, 504–522.
    [Google Scholar]
  10. LazearG.D.1993. Mixed‐phase wavelet estimation using fourth‐order cumulants. Geophysics58, 1042–1051.
    [Google Scholar]
  11. LichmanE. & NorthwoodE.J.1995. Phase inversion deconvolution for long and short period multiple attenuation. Geophysical Prospecting43, 469–486.
    [Google Scholar]
  12. LinesL.R. & UlrychT.J.1977. The old and the new in seismic deconvolution and wavelet estimation. Geophysical Prospecting25, 512–540.
    [Google Scholar]
  13. MarschallR. & KnechtM.1986. Reflectivity‐corrected deconvolution and its influence on inversion. Research Workshop on Deconvolution and Inversion, 3–5 September 1986, Rome, Italy.
  14. MatsuokaT. & UlrychT.J.1984. Phase estimation using the bispectrum. Proceedings of the IEEE72, 1403–1411.
    [Google Scholar]
  15. PolletA., LowrieL., MatthewsJ.1982. Vibroseis deconvolution – a surface‐consistent method. 52nd SEG meeting, Dallas, USA, Expanded Abstracts, session S6.4.
  16. PorsaniM.J. & UrsinB.1998. Mixed‐phase deconvolution. Geophysics63, 637–647.
    [Google Scholar]
  17. RistowD. & JurczykD.1975. Vibroseis deconvolution. Geophysical Prospecting23, 363–379.
    [Google Scholar]
  18. RobinsonE.A.1967. Predictive decomposition of time series with applications to seismic exploration. Geophysics32, 418–484.
    [Google Scholar]
  19. RobinsonE.A. & TreitelS.2000.Geophysical Signal Analysis. Society of Exploration Geophysicists, Tulsa. (Reprint of the 1980 edition.)
     [Google Scholar]
  20. RobinsonE.A. & WoldH.1963. Minimum‐delay structure of least‐squares and eo ipso predicting systems. In: Time Series Analysis (ed. M.Rosenblatt ), pp. 192–196. John Wiley & Sons, Inc.
     [Google Scholar]
  21. TygelM., HuckH., HubralP.1991. Mixed‐delay wavelet deconvolution of the point source seismogram. Geophysics56, 1405–1411.
    [Google Scholar]
  22. UlrychT.J. & MatsuokaT.1991. The output of predictive deconvolution. Geophysics56, 371–377.
    [Google Scholar]
  23. UlrychT.J. & WalkerC.1982. Analytic minimum entropy deconvolution. Geophysics47, 1295–1302.
    [Google Scholar]
  24. UrsinB. & PorsaniM.J.2000. Estimation of an optimal mixed‐phase inverse filter. Geophysical Prospecting48, 663–676.DOI: 10.1046/j.1365-2478.2000.00206.x
     [Google Scholar]
  25. WuenschelP.1965. Dispersive body waves: an experimental study. Geophysics30, 539–551.
    [Google Scholar]
  26. YilmazO.1987.Seismic Data Processing. Society of Exploration Geophysicists, Tulsa.
    [Google Scholar]
  27. ZiolkowskiA.1982. Further thoughts on Popperian geophysics – the example of deconvolution. Geophysical Prospecting30, 155–165.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.1046/j.1365-2478.2001.00260.x
Loading
  • Article Type: Research Article

Most Cited This Month Most Cited RSS feed

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