Estimating seismic dispersion from prestack data using frequency-dependent AVO analysis
Wu, X., Chapman, M. and Li, X.-Y., 2014. Estimating seismic dispersion from prestack data using frequency-dependent AVO analysis. Journal of Seismic Exploration, 23: 219-239. Recent laboratory measurement studies have suggested a growing consensus that fluid saturated rocks can have frequency-dependent properties within the seismic bandwidth. It is appealing to try to use these properties for the discrimination of fluid saturation from seismic data. In this paper, we develop a frequency-dependent AVO (FAVO) attribute to measure magnitude of dispersion from pre-stack data. The scheme essentially extends the Smith and Gidlow’s (1987) two-term AVO approximation to be frequency-dependent, and then linearize the frequency-dependent approximation with Taylor series expansion. The magnitude of dispersion can be estimated with least-square inversion. A high-resolution spectral decomposition method is of vital importance during the implementation of the FAVO attribute calculation. We discuss the resolution of three typical spectral decomposition techniques: the short term Fourier transform (STFT), continuous wavelet transform (CWT) and Wigner-Ville Distribution (WVD) based methods. The smoothed pseudo Wigner-Ville Distribution (SPWVD) method, which uses smooth windows in time and frequency domain to suppress cross-terms, provides higher resolution than that of STFT and CWT. We use SPWVD in the FAVO attribute to calculate the frequency-dependent spectral amplitudes from pre-stack data. We test our attribute on forward models with different time scales and crack densities to understand wave-scatter induced dispersion at the interface between an elastic shale and a dispersive sandstone. The FAVO attribute can determine the maximum magnitude of P-wave dispersion for dispersive partial gas saturation case; higher crack density gives rise to stronger magnitude of P-wave dispersion. Finally, the FAVO attribute was applied to real seismic data from the North Sea. The result suggests the potential of this method for detection of seismic dispersion due to fluid saturation.
- Aki, K. and Richards, P.G., 1980. Quantitative Seismology. W.H. Freeman and Co., SanFrancisco.
- Bath, M., 1974. Spectral Analysis in Geophysics. Elsevier science Publishers, Amsterdam.
- Castagna, J.P., Sun, S. and Siegfried, R.W., 2003. Instantaneous spectral analysis: detection oflow-frequency shadows associated with hydrocarbons. The Leading Edge, 22(3): 120-127.
- Chapman, M., 2003. Frequency dependent anisotropy due to meso-scale fractures in the presenceof equant porosity. Geophys. Prosp., 51: 369-379.
- Chapman, M., Liu, E. and Li, X.-Y., 2006. The influence of fluid-sensitive dispersion andattenuation on AVO analysis. Geophys. J. Internat., 167: 89-105.
- Claasen, T. and Mecklenbriicker, W., 1980. The Wigner distribution: a tool for time - frequencysignal analysis. Philips J. Res., 35: 217-250.
- Cohen, L., 1995. Time-Frequency Analysis. Prentice Hall Inc., New York.SEISMIC DISPERSION 239
- Dasgupta, R. and Clark, R.A., 1998. Estimation of Q from surface seismic reflection data.Geophysics, 63: 2120-2128.
- Gabor, D., 1946. Theory of communication. J.IEEE, 93: 429-457.
- Gardner, G.H.F., Gardner, G.L. and Gregory, A.R., 1974. Formation velocity and density - Thediagnostic basics for stratigraphic traps. Geophysics, 39: 770-780.
- Gist, G.A., 1994. Interpreting laboratory velocity measurements in partially gas-saturated rocks.Geophysics, 59: 1100-1109.
- Gurevich, B., Makarynska, D., de Paula, O. and Pervukhina, M., 2010. A simple model forsquirt-flow dispersion and attenuation in fluid-saturated granular rocks. Geophysics. 75(6):N109-N120.
- Hauge, P.S., 1981. Measurements of attenuation from vertical seismic profiles. Geophysics, 46:1548-1558.
- Mallat, S.G., 1999. A wavelet tour of signal processing. Academic Press Inc., New York.
- Miller, T.M. and Rothert, E., 2006. Seismic attenuation due to wave-induced flow: Why Q inrandom structures scales differently. Geophys. Res. Lett., 33: L16305.
- Murphy, W.F., 1982. Effects of partial water saturation on attenuation in massilon sandstone andvycor porous glass. J. Acoust. Soc. Am., 71: 1458-1468.
- Quan, Y. and Harris, J.M., 1997. Seismic attenuation tomography using the frequency shift method.Geophysics, 62: 895-905.
- Quintal, B. and Tisato, N., 2013. Modeling seismic attenuation due to wave-induced fluid flow inthe mesoscopic scale to interpret laboratory measurements. Sth Biot Conf. Poromechanics,Vienna: 31-40.
- Sinha, S., Routh, P.S., Anno, P.D. and Castagna, J.P., 2005. Spectral decomposition of seismicdata with continuous wavelet transform. Geophysics, 70(6): 19-25.
- Smith, G.C. and Gidlow, P.M., 1987. Weighted stacking for rock property estimation and detectionof gas. Geophys. Prosp., 35: 993-1014.
- Taner, M.T. and Treitel, S., 2003. A robust method for Q estimation. Expanded Abstr., 73rd Ann.Internat. SEG Mtg., Dallas: 710-713.
- Tonn, R., 1991. The determination of seismic quality factor Q from VSP data: A comparison ofdifferent computational methods. Geophys. Prosp., 39: 1-27.
- White, J.E., 1975. Computed seismic speeds and attenuation in rocks with partial gas saturation.Geophysics, 40: 224-232. 7
- Wilson, A., Chapman, M.,and Li, X.-Y., 2009. Frequency-dependent AVO inversion. Expanded
- Abstr., 79th Ann. Internat. SEG Mtg., 28: 341-345.
- Wilson, A., 2010. Theory and Methods of Frequency-Dependent AVO Inversion. Ph.D. Thesis,University of Edinburgh, Edinburgh.
- Wu, X. and Liu, T., 2009. Spectral decomposition of seismic data with reassigned smoothed pseudo
- Wigner-Ville distribution. J. Appl. Geophys., 68: 386-393.
- Wu, X., Chapman, M., Wilson, A. and Li, X.-Y., 2010. Estimating seismic dispersion frompre-stack data using frequency-dependent AVO inversion. Expanded Abstr., 80th Ann.Internat. SEG Mtg., Denver, 29: 341-345.
