Nonlinear AVO inversion using particle filter
粒子滤波非线性AVO反演方法

This paper presented a new method for AVO nonlinear inversion that resolves AVO Bayesian nonlinear inversion using particle filter(PF).The key idea is to represent the required posterior density function by a set of random samples with associated weights and to compute estimates based on these samples and weights.First the basic principle of PF is dissertated, include state transmission model and observation model,weights updating and prediction, importance density sampling,etc.Then the state transmission and observation model are established for AVO inversion.Finally,both synthetic and real data are inverted using the PF. The inversion results show that the proposed method is robust and has wide application potential for AVO inversion.Meanwhile it can provide a new approach to solve the other inversion problem of geophysics.