本文将AVO数据反演纳入贝叶斯统计网络的框架。借助这一网络。运用正演问题的模型参数和物理特性生成了合成记录,然后将该合成记录与观测的数据进行拟合,以求得该模型参数的后验概率密度函数(PPD)。遗传算法(GA)中用定向随机搜索方法估算了PPD的形状。与经典反演方法不同,GA不取决于起始模型的选择,它很适合于AVO反演。单层AVO反演是对单层反射同相轴的振幅进行反演,GA This paper incorporates AVO data inversion into Bayesian statistical network framework. With this network. Synthetic records were generated using the model parameters and physical properties of the forward problem, and then the synthetic records were fitted with the observed data to obtain the posterior probability density function (PPD) of the model parameters. Genetic algorithm (GA) using directional random search method to estimate the shape of the PPD. Unlike classical inversion methods, GA does not depend on the choice of starting model and is well suited for AVO inversion. Single-layer AVO inversion is the inversion of the amplitude of single-layer reflection events, GA