Influence of frequency and saturation on AVO attributes for patchy saturated rocks

Abstract

Partially saturated rocks are considered to be major sources of seismic wave velocity dispersion and attenuation in recorded real data. From the physical description of partially saturated gas-water and oil-water reservoirs, we use upscaling theories to compute an equivalent frequency-dependent porous medium. These homogenization methods are associated with mesoscale description of attenuation and dispersion coming from wave-induced flow phenomena. To compute wave propagation, we use numerical codes in the frequency domain that allow us to take into account all the frequency-dependent parameters without approximation or local time steps. In this way, the Biot slow compressional wave is well modeled and its partially diffusive, partially propagative behavior is completely considered. The attenuation and dispersion of the waves in such media are coming partly from the wave mode conversion into diffusive slow waves, not visible on seismograms. But the amplitude of propagative P- and S-waves are mainly affected by these energy losses at interfaces. Using full waveform modeling, we investigate the amplitude versus offset (AVO) attributes with respect to saturation and frequency. For a simple three-layer case, we compute poroelastic wave propagation, extract maximum amplitude with respect to angle, and, through a least-square fitting method, we obtain the AVO attributes for PP- and PS-reflected events. Due to the influence of mesoscale induced-flow phenomena and relatively to the regime of the Biot slow wave, the main results show a strong variability of the AVO attributes with the frequency and a lower variability with the saturation for reflected PP or PS events. We show that gas-water and oil-water systems have similar behaviors. Strong differences between patchy saturation and effective fluid phase theories are highlighted, especially at high frequency, for PP events and for gas-water systems. Then, we conclude that these AVO attributes carry information about the saturation that can be used to estimate the saturation variations in time-lapse studies.