Nonlinear FAVO Dispersion Quantification Based on the Analytical Solution of the Viscoelastic Wave Equation
Nonlinear FAVO Dispersion Quantification Based on the Analytical Solution of the Viscoelastic Wave Equation
复制标题
基于粘弹性波方程解析解的非线性FAVO色散量化
DOI：
10.1155/2020/7616045
复制
发表时间：
2020
期刊：
影响因子：
1.7
通讯作者：
Tang Wei
中科院分区：
文献类型：
--
作者：
Li Yuanqiang;Li Jingye;Chen Xiaohong;Zhang Jian;Zhou Chen;Tang Wei
Wave-induced fluid flow is the main cause of seismic attenuation and dispersion. So the estimated velocity dispersion information can be used to identify reservoir fluid and effectively reduce the risk of reservoir drilling. Using equivalence of dispersion and attenuation between poroelastic and viscoelastic media, we developed the method of FAVO (frequency-dependent amplitude variation with offset) dispersion quantitative estimation based on the analytical solution of 1D viscoelastic wave equation. Compared with the current single-interface velocity dispersion estimation method, the new nonlinear approach uses the analytical solution of 1D viscoelastic wave equation as the forward modeling engine. This method can conveniently handle the attenuation and generate the full-wave field response of a layered medium. First, the compound matrix method (CMM) was applied to rapidly obtain the analytical solution by vectorization. Further, we analyzed the seismic response characteristics through the model data to clarify the effectiveness of the forward modeling method. Then, the more reliable P-wave velocity, S-wave velocity, and density were recovered based on prestack viscoelastic waveform inversion (PVWI). Combining with the inversion results, the derivative matrix was calculated to perform nonlinear velocity dispersion estimation. Finally, the new estimation method was tested with the model and actual data. The experiments show that the developed method is clearly superior to the single-interface dispersion estimation method in accuracy and resolution. This approach can be used as a new choice reservoir fluid identification.
