Seismic Frequency Component Inversion for Elastic Parameters and Maximum Inverse Quality Factor Driven by Attenuating Rock Physics Models

Attenuation exists in seismic wave propagation in subsurface layers, and relatively high attenuation occurs in oil-bearing reservoirs. Inversion of frequency components of observed seismic data generates values of attenuation factor 1/Q, which produces potential results for determining oil-bearing reservoirs. Beginning with expressions of seismic wave velocity in attenuating media, we involve P-wave maximum attenuation factor to rewrite P-wave velocity driven by an attenuating rock physics model, and we also employ an empirical relationship between P-wave attenuation factor and S-wave attenuation factor to express S-wave velocity in terms of P-wave maximum attenuation factor. Using the derived P- and S-wave velocities, we extend Zoeppritz equations to compute reflection coefficient for an interface separating two attenuating media. Under the assumption that contrasts in elastic properties of two media across the interface are small and the background attenuation is weak, we propose a linearized reflection coefficient of PP-wave as a function of contrasts in elastic parameters (i.e., P-wave velocity, S-wave velocity and density) and attenuation factor, and expression of elastic impedance (EI) is also presented. Based on the EI, we demonstrate an approach of estimating elastic parameters and attenuation factor from frequency components of partially incidence-stacked seismic data, which is implemented as a two-step inversion involving the prediction of EI datasets using a model-based damping least-squares algorithm and nonlinear inversion for elastic parameters and attenuation factor. Noisy synthetic seismic data generated using the extended Zoeppritz equations are employed to verify the robustness and stability of the proposed inversion approach. Applying the proposed approach to a real dataset acquired over an oil-bearing reservoir, we obtain convincing results of P-wave velocity, S-wave velocity, density and attenuation factor, which can reasonably match corresponding well log data.