A novel prestack AVO inversion and its application

Abstract

Prestack AVO inversion is multidimensional and ill posed, and is often strongly affected by noise and measurement uncertainty, so it is necessary to performing constraints in order to obtain steady and rational inversion results. A novel prestack AVO inversion method is developed based on linearized approximation of the Zoeppritz equation and Bayesian parameter estimation theory. Covariance matrix is used to describe the correlation degree between the parameters, Gaussian distribution is used for likelihood function and modified Cauchy distribution is used for prior distribution; P‐wave impedance, S‐wave impedance, density and rock physics relation are applied to constrain the inversion results, thus it is reliable to make the result more accurate and steady. Tests on synthetic and real data show that all inverted parameters are almost perfectly retrieved even the SNR is low.