Abstract：Stochastic inversion of elastic impedance based on Metropolis sampling algorithm is a Monte Carlo based strategy for non-linear inversion,which can effectively integrate the high-frequency information of well-logging data and have a higher resolution.This method is formulated in the Bayesian framework.Firstly,the priori information can be obtained through Fast Fourier Transform-Moving Average (FFT-MA) and Gradual Deformation Method (GDM).Then Metropolis algorithm is employed so as to obtain an exhaustive characterization of the posteriori probability density.FFT-MA is a kind of efficient simulation method.Combined with GDM,it can constantly modify the reservoir model and keep the spatial structure unchanged until it matches the observed seismic data.According to the numerical calculations,it can be concluded that FFT-MA simulation can reduce the time consumption.Combined with GDM updating algorithm,the inversion results can converge rapidly,and the final results match the model well and have a higher resolution.In addition,this method adopts two-step method to invert elastic parameters,so it improves the computational efficiency to some extent.
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