High-order AVO inversion for effective pore-fluid bulk modulus based on series reversion and Bayesian theory

Abstract

Pore-fluid identification is one of the key technologies in seismic exploration. Fluid indicators play important roles in pore-fluid identification. For sandstone reservoirs, the effective pore-fluid bulk modulus is more susceptible to pore-fluid than other fluid indicators. AVO (amplitude variation with offset) inversion is an effective way to obtain fluid indicators from seismic data directly. Nevertheless, current methods lack a high-order AVO equation for a direct, effective pore-fluid bulk modulus inversion. Therefore, based on the Zoeppritz equations and Biot-Gassmann theory, we derived a high-order P-wave AVO approximation for an effective pore-fluid bulk modulus. Series reversion and Bayesian theory were introduced to establish a direct non-linear P-wave AVO inversion method. By adopting this method, the effective pore-fluid bulk modulus, porosity, and density can be inverted directly from seismic data. Numerical simulation results demonstrate the precision of our proposed method. Model and field data evaluations show that our method is stable and feasible.