Estimation of 2D Stationary Random Medium Parameters from Post‐Stack Seismic Data

Abstract

AbstractThe key to apply the random medium theory to seismic exploration is the estimation of random medium parameters (RMP) from seismic data. In this paper, we propose an approach to estimate parameters of 2D stationary random medium from post‐stack seismic data (PSD). Firstly, the relationship between PSD and the impedance model of random medium is established, and the principle and method of parameters estimation of autocorrelation function (ACF) are introduced. Then, by using power spectrum method, the algorithms and procedures for estimating RMP are discussed with an example; afterward, the feasibility and correctness of this approach is tested using several 2D theoretical models; finally, this approach is applied to the field seismic data, and the results indicate that the estimated parameters can provide an important reference for further dividing delta sedimentary facies, which reflects the estimation method of RMP is very promising. Compared with peer‐research work, the estimation method in this paper is a real 2D algorithm, and in particular it can estimate the autocorrelation angle, and this approach based on power spectrum method is obviously efficient and easily understandable. However, we could not ignore the relatively large errors in our approach, and it needs to be further improved and amended in the later researches.