Nonlinear Elastic Impedance Inversion in Laplace–Fourier Domain

Abstract

The elastic impedance (EI) inversion plays an important part in prestack seismic inversion. Compared with the linear EI equation, a novel nonlinear EI equation is derived, and the equation is more accurate and suitable for high-contrast situations. The conventional EI inversion approach faces the enormous challenges of estimating elastic parameters correctly and effectively when there is no well-log data or prior geophysical information to establish the EI initial models. In view of this problem, considering the phenomenon of the low-frequency amplitude and the proportion of low-frequency energy increase with the damping factor in the Laplace–Fourier domain, the low-frequency components can be recovered by the proposed EI inversion approach with Bayesian inference in the Laplace–Fourier domain and as the initial models further used in the conventional time-domain EI inversion. P- and S-wave impedances are extracted by combining artificial neural network inversion tool and the novel EI equation. The sensitivity analysis shows that the novel nonlinear EI equation is more sensitive to impedances rather than density. The field data examples demonstrate that our approach is feasible.