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Parameter estimation of non-stationary random media driven by partially stacked seismic data

Lin Ying, Zhang Guangzhi, Chen Siyuan, Huang Minmin, Wang Baoli

Acta Geophysica

2022

Vol. 70, no 5

2119--2133

The estimation of non-stationary random medium parameters is the key to the application of random medium theory in fine seismic exploration. We propose a method for estimating non-stationary random medium parameters from partially stacked seismic data. To begin with, the relationship between seismic data and random medium p-wave velocity, s-wave velocity, density model in random medium is described, and the principle and method of estimating the parameters of autocorrelation function of random medium are introduced in this paper. Subsequently, the specific steps of applying the power spectrum method for non-stationary random media parameter estimation are also presented. The feasibility and correctness of the method are verified through the estimation test of the two-dimensional theoretical model. Eventually, the estimation test of non-stationary random medium parameters is carried out by field seismic data. The results show that the non-stationary random medium parameters can better describe the elastic parameter information of the subsurface media and provide a reference for the initial model construction of the elastic parameters, reflecting that the method has good application prospects. Compared with previous studies, this method extends the random medium parameter estimation from stationary to non-stationary and from single wave impedance random medium parameter to multi-elastic parameter random medium parameters. It provides a basis for the in-depth application of random media theory in field data. Meanwhile, this estimation method based on the power spectrum method has the advantage of being intuitive and easy to interpret. However, there are also problems in smoothing effect, which needs further improvement and refinement.