Since most of the information on S-waves and density exists in the middle to large angle range of seismic data, traditional inversion methods based on the Zoeppritz approximation have difficulty in obtaining satisfactory results. Therefore, as a high accuracy AVA inversion, exact Zoeppritz (EZ) equation inversion has aroused a lot of attention in recent years. As for any other non-linear inversion, iterative convergence and error are the important problems. In this abstract, based on a Bayesian framework, we have introduced optimal transport into exact Zoeppritz equation AVA inversion. Then the L-BFGS method is adopted to solve the regularization-constrained least-square argument function to obtain the inversion results, including P-wave velocity, S-wave velocity and density. We compare this method with a conventional method, which is based on a L2 norm or weighted L2 norm as a residual method in the model test. The results show that the proposed method not only reduces the error of the results to be smaller than L2 norm, but it also improves the convergence rate.


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