Direct Estimation Of Petro-physical Properties Based On AVO Inversion

The purpose of using geophysical methods for reservoir characterization usually goes beyond estimating the elastic parameters.Rather,the ultimate goal is to deter mine petro-physical properties(porosity,clay content,water saturation and permeability).Reservoir properties play an important role in reservoir characterization.Reliably estimating petro-physical properties is crucial for the exploration and development of hydrocarbon reservoir because these parameters provide information for field appraisal and selection of optimal well location.Currently,the seismic interpretation technology has become a common tool in exploration and reservoir characterization.Seismic data contain invaluable sources of reservoir information and seismic inversion provides the geophysicists with an efficient approach to obtain these reservoir parameters.Seismic amplitude information has become more reliable to conduct reservoir characterization with improved certainty and in a more efficient way.The conventional estimation of reservoir properties from seismic inversion based on Bayesian theory is implemented in a sequential approach.First,seismic data are routinely inverted into elastic parameters;and then,rock-physics models derived from well log statistics and analysis transform these elastic parameters to the petro-physical properties.It is obviously an indirect way to predict petro-physical properties from seismic data.Estimation of reservoir properties from inverted elastic parameters,will lead to errors due to propagation of previous inversion errors.The indirect way of petro-physical properties estimation from seismic data causes much more bias,uncertainty and accumulated errors,which reduces the prediction accuracy of reservoir properties.We combined rock physics model and Aki-Richards equation in one system to derive a generalized AVO approximation in terms of porosity,clay content and density.The new formulation directly links pre-stack seismic data and reservoir properties and provides the direct estimation of these petro-physical properties from seismic data.Based on Bayesian theory,we develop a robust AVO inversion approach and apply it to model and real data sets.Tests on synthetic data show that reasonable petro-physical properties can directly be estimated from seismic data and the proposed method avoids the accumulated error from indirect transformation.The stable inversion results can be obtained under circumstance with different noise levels,which represents better anti-noise performance.Practical seismic data application effect also indicates that the estimated petro-physical properties are in good agreement with the well data,which manifests the applicability of the proposed inversion method.