Resolution Enhancement of Robust Bayesian Pre-stack Inversion in the Frequency Domain

Abstract

In this paper, one novel robust Bayesian pre-stack AVO inversion in the frequency domain is proposed which could solve the instability and achieve superior resolution. The Fourier operator will be integrated into objective equation and it avoids the Fourier inverse transform in the inversion process. Furthermore, the background constraints of model parameters are taken into consideration to improve the stability and reliability of inversion which could compensate the low frequency components of seismic signal. Besides, the different frequency components of seismic signals can realize decoupling automatically. This will help us to solve the inverse problem by the means of multi-components successive iteration. So, superior resolution compared with the conventional time-domain pre-stack inversion could be achieved easily. The synthetic tests illustrate that the proposed method could achieve high-resolution results winning a high degree of agreement with the theoretical model and verify the quality of anti-noise. Finally, applications on field data case demonstrate that the proposed method could obtain stable inversion results of elastic parameters from pre-stack seismic data in conformity with the real logging data.