Pre-stack stochastic inversion based on hybrid genetic algorithm

Key words:  hybrid genetic algorithm  pre-stack stochastic inversion  resolution  convergence

Abstract:

This paper proposed a pre-stack stochastic inversion method based on a hybrid genetic algorithm aiming to resolve the problem of low computation efficiency. It makes full use of the high frequency information of well logging data and is constrained by seismic data at the same time. Firstly, it obtains the geostatistical simulated results through the fast Fourier transform-moving average (FFT-MA) spectrum simulation, and then optimizes the initial simulated results using the hybrid genetic algorithm (HGA) proposed by this paper to obtain the inversion results that correlate with the geological structure. HGA can overcome the drawbacks of conventional genetic algorithm(GA), such as slow convergence and "premature". It can obtain the optimal results quickly when combined with simulated annealing (SA). The numerical testing shows that the pre-stack stochastic inversion based on hybrid genetic algorithm can ensure the convergence of the inversion and also satisfy well data. In addition, this method has high vertical resolution compared with the conventional pre-stack inversion, and may play an important role in reservoir identification and reservoir description.