PP- & PS-wave prestack nonlinear inversion based on adaptive MCMC algorithm
Zhang Guangzhi1,2, Pan Xinpeng1, Sun Changlu1, Yin Xingyao1,2
1. School of Geosciences, China University of Petroleum(East China), Qingdao, Shandong 266580, China;
2. Laboratory of Marine Mineral Resources, Qingdao National Laboratory of Marine Science and Technology, Qingdao, Shandong 266071, China
Abstract：Through amplitude versus offset (AVO) inversion, we can obtain elastic parameters related to reservoir lithology and fluid content. However, the solutions of prestack inversion with PP data only are quite unstable, so the joint application of PP and PS seismic data could further reduce the non-uniqueness of the inversion, and greatly improve its stability and accuracy of the inversion. In this article, we develop a new method of joint prestack nonlinear inversion of PP and PS waves based on the adaptive Markov chain Monte Carlo (MCMC) algorithm, and it can be used for inverting three parameters including P- and S-wave velocities and density via the exact Zoeppritz equation. Based on Bayesian framework, logging-constrained priori information is introduced in the inversion process. Then we sample posterior probability density and apply the adaptive MCMC algorithm to obtain the posterior probability density of AVO three parameters by making statistical analysis of these random samples. Finally, we analyze the uncertainty of AVO inversion results of three parameters. Tests on synthetic data show that all three parameters are well retrieved, and the proposed method is quite stable, accurate, and anti-noise, which demonstrates its reliability and effectiveness.
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