纵横波联合叠前自适应MCMC反演方法

PP-& PS-wave prestack nonlinear inversion based on adaptive MCMC algorithm

联合纵波(PP波)和转换波(PS波)地震资料进行AVO反演可降低解的非唯一性,提高反演的稳定性和AVO参数估算精度。文中提出了一种基于自适应马尔科夫链蒙特卡洛(MCMC)的纵横波叠前联合非线性反演方法,直接反演纵、横波速度及密度三个参数。该方法基于精确Zoeppritz方程,在贝叶斯框架下引入测井约束先验信息,在反演过程中使用自适应MCMC方法对贝叶斯后验概率密度进行抽样,并通过对收敛于后验概率密度随机样本的统计分析,获取表征纵、横波速度及密度参数的后验概率密度信息。同时对其AVO三参数反演结果进行不确定分析,可用于储层流体检测与岩性识别的风险评估。实际井模型数据测试结果表明,基于精确Zoeppritz方程的自适应MCMC法纵横波叠前联合反演精度较高、稳定性较好、抗噪能力也较强,验证了方法的可行性和有效性。

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. © 2016, Editorial Department OIL GEOPHYSICAL PROSPECTING. All right reserved.