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 (1987)’s 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-Vill 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.
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