Pre-stack Elastic Impedance Inversion Based On Bayesian Theory

Post-stack acoustic impedance inversion uses multi-stacked seismic data,therefore,it weakens the sensitivity of reservoir characteristics reflecting.Moreover,post-stack inversion can only provide PP wave impedance parameters,and the research in terms of lithology and fluid has been limited.In contrast,pre-stack inversion technique is an effective method of seismic inversion.We can get the subsurface elastic parameters information via the inversion,and then predict the lithology and identify fluid.This paper studies pre-stack elastic impedance inversion theory using different angles gathers,and Bayesian theory is introduced in the inversion process.This paper studies PP wave,joint PP wave and PS wave and VTI media elastic impedance inversion methods.This paper derives and analyzes elastic impedance equation at first,and focuses on characteritics of elastic impedance with different angles on the great changes of dimensionless,and then we standardize elastic impedance formula.Then accuracy of three different elastic impedance formulas is compared.We give the elastic impedance inversion algorithm based on the theory of post-stack impedance inversion,and Bayesian theory was introduced in the inversion algorithm.According to inversion algorithms of different conditions,this paper selects the corresponding formula,and does the inversion of PP wave,joint PP and PS wave and VTI media elastic impedance.Numerical tests are done for different models,and get better inversion results.In order to get more lithologic parameters,this paper studies the pre-stack elastic parameters,and normalized formula.We can directly get results of P-wave velocity,S-wave velocity,and density from the inversion data,which are more accurate than results obtained from the conventional methods.It provides an effective means for the study of the underground reservoir lithology and fluid properties.Results of model data inversion show that the elastic impedance inversion can extract various lithologic parameters directly.And thus reservoir identification and prediction can be fulfilled by the lithologic information.