1887
Volume 26, Issue 2-3
  • ISSN: 0812-3985
  • E-ISSN: 1834-7533

Abstract

Traditional seismic processing methods such as CMP stacking and predictive deconvolution often fail in the attenuation of long period multiples. Stacking often fails due to the lack of velocity differentiation between the multiple and surrounding events and because of the amplitude of the multiple reflections. Predictive deconvolution and Event Prediction (DePledge and Uren, 1992) fail because of the non-periodic nature of the multiples and to a lesser extent because of the variation of the wavelet with angle of incidence.

A four step procedure to precondition and attenuate surface related long period multiples has been devised. The first two steps of this procedure solve both the periodicity problem and the variation of wavelet with angle of incidence. The third step, therefore, is the attenuation of the surface related multiples using the standard techniques mentioned above. The remaining step is to reverse the transforms applied in the first two steps.

An example is given to demonstrate the performance of this method on field data. The procedure is simple, fast to apply and gives results superior to other existing techniques.

© 1995 ASEG
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1995-06-01
2026-01-13

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References

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  2. Backus, M. M., 1959, Water reverberations - their nature and elimination: Geophysics, 24, 233-261.
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  10. Riley, D. C, and Claerbout, J. R, 1976, 2-D multiple reflections: Geophysics, 41, 592-620.
  11. Taner, M. T., 1980, Long Period Multiples and their suppression: Geophysical Prospecting, 28, 30-48.
  12. Tsai, C. J., 1985, Use of autoconvolution to suppress first order, long period multiples: Geophysics, 50, 1410 - 1425.
  13. Verschuur, D. J., 1991, Surface related multiple elimination: an inversion approach: Ph.D. thesis, Delft University of Technology, The Netherlands.
  14. Wiggins, J. W., 1988, Attenuation of complex water bottom multiples by wave equation base prediction and subtraction: Geophysics, 53, 1527 - 1539.
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  • Article Type: Research Article
Keyword(s): Event Prediction and Predictive Deconvolution; Multiple Moveout; Multiples; Radial Trace Transform

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