基于贝叶斯理论的逐次迭代非线性AVA反演方法

常规AVA三参数反演方法均基于横波速度与纵波速度之比γ为常数这一假设条件，且常被近似地取为0.5。然而在许多情况下γ并不为常数，而是在横向与纵向都渐变。若一概假定γ等于0.5，反演出的岩性参数势必要偏离真实值，因此有必要合理地选择γ。笔者基于贝叶斯理论，提出逐次迭代非线性AVA的反演方法。该方法把γ看成横向与纵向都渐变的反演初始背景，通过给定初始模型计算初始背景γ，并采用逐次迭代的策略求解该反演问题,解决了关于γ的选取问题以及由于引入变γ值而带来的非线性问题，提高了AVA三参数反演结果的精确度。

Non-Linear Pre-Stack Seismic AVA Inversion Based on Bayesian Theory Using Successive Iteration Method

Conventional three-term AVA inversion methods are based on the assumption that γ (the ratio of S-wave velocity to P-wave velocity) is a constant value usually considered to be 0.5, while γ is horizontally and vertically varied gradually in many cases. The estimated parameters of the inversion is bound to deviate from its true values with γ invariably being 0.5.  and the selection γ  needs to be reasonably. Based on Bayesian theory, we presents a nonlinear pre-stack seismic AVA inversion using successive iterative method, which considered the ratio’s initial background varying horizontally and vertically and being calculated by the-given initial model, and the nonlinear inversion problem was solved by successive iteration. The proposed method gived a reasonable solution for the selection of γ and solved the nonlinear problem caused by variable ratio γ . And the accuracy and stability of the three-term AVA inversion were improved.