Study Of Anisotropic Rock Physics Model And Application

Rock physics model is the bridge of well log, seismic attributes and parameters of resevior. The precision of the rock physics model affectes the well logging interpretation and seismic interpretation. Now most rock physics models are semiempirical models and only suit for isotropic rock. While some rocks are anisotropic, they can not be approximlately described as isotropic model. It is valuable in theory and application to establish anisotropic rock physics model. In the thesis a isotropic dual porosity (IDP) model is developed based on isotropic self-consistent approximation (SCA) , differential effective medium (DEM) and fluid substitution. The velocities of rock are accurately predicted by IDP effective medium model. And compared with the prediction of Xu-White model the IDP is more accurate. To predict rock properties and shear wave velocity in anisotropic rocks anisotropic effective medium model of pure shale is developed based on the anisotropic SCA, DEM and fluid substitution. When anisotropic effective medium is applied to shaly sand anisopic dual porosity (ADP) model is developed. In the ADP the elastic properties of clean sandstone and pure shale are calculated by anisotropic model. And the effect induced by pores aspect ratio and clay constant in rock is simulated by ADP model.The result of numerical simulation suggests that the ADP is more accurate the IDP. ADP is applied to model the different distributions of clay in shaly sand, and the effect of different distribution of clay is studied. Three anisotropic effective medim models are developed according to different distribution of clay. The anisotropic effective medium is combined with rock physics diagnostics to predict S-waves velocity. The result indicts that the estimation of velocity is exact. Furthermore the technology is applied to detect the type of fluid in complicate reservoir. The different responses of elastic properties of rocks are calculated by changing the pore fluid. The type of fluid can be detected by comparing the data from measurement with the data form calculation. The technology is applied to field data, and it works well.