Reservoir Characterization Based on Bayesian Amplitude Versus Offset Inversion of Marine Seismic Data - Jianhua Wang; Xinpeng Pan; Wenbo Sun; Chao Li; Ying Zheng; Xiaolong Zhao (Journal of Marine Science and Engineering)
Young’s modulus and Poisson’s ratio are critical parameters for reservoir characterization using marine seismic data. Conventional amplitude versus offset (AVO) inversion methods often assume a constant S-to-P wave velocity ratio to simplify the inversion, leading to significant errors, particularly in heterogeneous reservoirs. To address this, we derive a novel four-term PP-wave reflection coefficient by reparameterizing Poisson’s ratio, effectively reducing the nonlinearity associated with the velocity ratio and enhancing the stability of Poisson’s ratio estimation. Building on this, we propose a Bayesian AVO inversion framework incorporating Cauchy prior and low-frequency model regularizations. The elastic parameters are estimated using a maximum a posteriori (MAP) approach by minimizing the negative log-posterior function. Numerical simulations and seismic gather data from East China demonstrate that the proposed inversion method yields more accurate estimates of Young’s modulus and Poisson’s ratio compared to conventional approaches. This improved AVO approximation offers a more reliable tool for delineating reservoir heterogeneity in complex geological settings using marine seismic data.