AccScience Publishing / JSE / Article
Submit to JSE
Cite this article
65
Views
Journal Browser
Volume | Year
Issue
Search
Forthcoming Issue
Current Issue
View All
News and Announcements
View All
ARTICLE

Analysis of seismic spectral attenuation based on Wigner-Ville distribution for sandstone reservoir characterization – a case study from West Sichuan Depression, China

XIOYANG WU,  TIANYOU LIU
Show Less
Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan, Hubei 430074, P.R.China,
JSE 2010, 19(1), 69–85;
Submitted: 1 July 2009 | Accepted: 2 October 2009 | Published: 1 January 2010
© 2010 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Download PDF
Cite
XML
Abstract

Wu, X. and Liu, T., 2010. Analysis of seismic spectral aitenuation based on Wigner-Ville distribution for sandstone reservoir characterization - a case study from the West Sichuan depression, China. Journal of Seismic Exploration, 19: 69-85. A mass of previous work has shown the application of seismic spectral decomposition for low frequency shadows detection and stratigraphic mapping. In this paper, we further analyze the characteristics of spectral attenuation in fractured sandstone reservoirs saturated with different fluids by Wigner-Ville distribution (WVD) based method. We give a description on the geometric structure of cross-terms due to bilinear nature of WVD with a multicomponent signal composed of three Gaussian time-frequency atoms. Then cross-terms are eliminated using improved WVD with time and frequency independent Gaussian kernels as smoothing windows, what is called the smoothed pseudo WVD (SPWVD). At last the SPWVD is applied to spectral decomposition of seismic data from West Sichuan depression of China. We focus our study on the comparison of characteristics of spectral attenuation in order to verify whether SPWVD can differentiate different fluids content. It shows that prolific gas reservoirs show higher peak spectral amplitude at higher peak frequency, which attenuate faster than low quality gas reservoirs and dry or wet reservoirs. SPWVD is able to separate prolific gas reservoirs from low-quality gas reservoirs and dry or wet reservoirs. This can be regarded as a spectral attenuation signature for future exploration in the study area.

Keywords
Wigner-Ville distribution
Gaussian kernel function
spectral attenuation
fluids
fractured sandstone reservoir
References
  1. Boudreaux-Bartels, G. and Wiseman, P., 1987. Wigner distribution analysis of acoustic well logs.
  2. Acoust., Speech, and Signal Proces., IEEE Internat. Conf. on ICASSP ’87, 12: 2237- 2240.
  3. Castagna, J.P., Sun, S. and Siegfried, R.W., 2003. Instantaneous spectral analysis: Detection oflow-frequency shadows associated with hydrocarbons. The Leading Edge, 22: 120-127.
  4. Chapman, M., Liu, E. and Li, X-Y, 2005. The influence of abnormally high reservoir attenuationon the AVO signature. The Leading Edge, 24: 1121-1125.
  5. Chen, G., (ALL NAMES), 2008. Spectral-decomposition to reservoir fluids from a deepwater WestAfrica reservoir. Geophysics, 73: 23-30.
  6. Choi, H.I. and Williams, W.J., 1989. Improved time frequency representation of multicomponentsignals using the exponential kernels. IEEE Transac. Signal Proces., 37: 862-871.
  7. Claasen, T. and Mecklenbrauker, W., 1980. The Wigner distribution: a tool for time-frequencysignal analysis. Philips J. Res., 35: 217-250.
  8. Cohen, L., 1995.Time-frequency analysis. Prentice Hall Inc., New York.
  9. Ebrom, D., 2004. The low frequency gas shadows in seismic sections. The Leading Edge, 23: 772.
  10. Goloshubin, G.M. and Korneev, V.A., 2000. Seismic low frequency effects for fluid saturatedporous media. Expanded Abstr., 70th Ann. Internat. SEG Mtg., Calgary, Alberta: 976-979.
  11. Goloshubin, G.M.. Korneev, V.A. and Vingalov, V.M., 2002. Seismic low-frequency effects fromoil-saturated reservoir zones. Expanded Abstr., 72nd Ann. Internat. SEG Mtg., Salt LakeCity: 1813-1817.WIGNER-VILLE DISTRIBUTION 85
  12. Goloshubin, G.M., (ALL NAMES), 2006. Reservoir imaging using low frequencies of seismicreflections. The Leading Edge, 25: 527-531.
  13. Hauge, P.S., 1981. Measurements of attenuation from vertical seismic profiles. Geophysics, 46:1548-1558.
  14. Korneev, V.A., (ALL NAMES), 2004. Seismic low frequency effects in monitoring fluid-saturatedreservoirs. Geophysics, 69: 522-532.
  15. Li, Y. and Zheng, X., 2008. Spectral decomposition using Wigner-Ville distribution withapplications to carbonate reservoir characterization. The Leading Edge, 28: 1050-1057.
  16. Liu, E., (ALL NAMES), 2006. Applications of spectral decomposition for AVO analyses in thewest of Shetland. Expanded Abstr., 76th Ann. Internat. SEG Mtg., New Orleans: 279-282.
  17. Moriya, H. and Niitsuma, H., 1996. Precise detection of a P-wave in low S/N signal by usingtime-frequency representations of a triaxial hologram. Geophysics, 61: 1453-1466.
  18. Novak, P. and Novak, V., 1993. Time/frequency mapping of the heart rate, blood pressure andrespiratory signals. Med. Biol. Eng. Comput. 31: 103-110.
  19. Partyka, G., Gridley, J. and Lopez, J., 1999. Interpretational applications of spectral decompositionin reservoir characterization. The Leading Edge, 18: 353-360.
  20. Rauch-Davies, M. and Ralston, M., 2005. Spectral decomposition - transform methods and fluid andreservoir prediction case study. 67th EAGE Conf., Madrid.
  21. Ralston, M., (ALL NAMES), 2007. General method to reduce crossterm interference in the
  22. Wigner- Ville decomposition. Expanded Abstr., 77th Ann. Internat. SEG Mtg., San Antonio:870-874.
  23. Sams, M.S., Neep, J.P., Worthington, M.H. and King, M.S., 1997. The measurement of velocitydispersion and frequency-dependent intrinsic attenuation in sedimentary rocks. Geophysics,62: 1456-1464.
  24. Silin, D.B., (ALL NAMES), 2004. A hydrologic view on Biot’s theory of poroelasticity. Lawrence
  25. Berkeley National Lab. Paper-54459, Univ. of California.
  26. Sinha, S.P., (ALL NAMES), 2005. Spectral decomposition of seismic data with continuous-wavelettransform. Geophysics, 70: 19-25.
  27. Taner, T.H., Koehler, F. and Sheriff, R.E., 1979. Complex seismic trace analysis. Geophysics, 44:1041-1063.
  28. Tang, J., Zhang, S. and Li, X.-Y., 2008. PP and PS seismic response from fractured tight gasreservoirs: a case study. J. Geophys. Engin., 5: 92-102.
  29. Wang, Y., 2007. Seismic time-frequency spectral decomposition by matching pursuit. Geophysics,72: 13-20.
  30. Wu, X. and Liu, T., 2009. Spectral decomposition of seismic data with reassigned smoothed pseudo
  31. Wigner-Ville distribution. J. Appl. Geophys., 68: 386-393.
Share
Back to top
Journal of Seismic Exploration, Print ISSN: 0963-0651, Published by AccScience Publishing
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here
Accept