Seismic Rock Physics Study Of Shale Reservoirs Based On The Statistical Theory

Shale has become an area of interest for unconventional hydrocarbon exploration.It is important to provide accurate and abundant parameters for shale reservoir characterization.The identification of lithology and fluid property by using seismic data is essential for reservoir characterization.However,parameters for different lithology always have overlap.The Bayesian theory is an available method to solve this problem.Besides,underground medium has continuity.The Markov chain and random filed can provide prior information of the lithology,which will improve the identification of lithology based on the Bayesian theory.Reservoir parameter inversion by using seismic data is more complicated.At first,a rock physics model is necessary to link the reservoir petrophysical parameters and anisotropy parameters.Then,the reservoir parameter inversion is processed by using elastic parameters which are obtained from seismic data.But there is uncertainty during the inversion,including noises of seismic data and errors of rock physics model.We build a stochastic rock physics model to link the reservoir petrophysical parameters and elastic parameters,then get the prior information from well data and well inversion result.Finally,the P-and S-wave impedances are translated into reservoir petrophysical parameter and anisotropy parameter sections.In the inversion process,the posterior probability distribution function(PDF)is achieved by using the Bayesian theory.Then the estimation of parameters and uncertainty of the inversion can be calculated from the posterior PDF.The uncertainty from seismic data and rock physics model are all taken account.The SA-PSO algorithm which combines the simulated annealing method and the particle swarm optimization method is used to get the maximum posterior probability.The algorithm is efficient and accurate in the optimization process.The stochastic inversion workflow is used in the Longmaxi shale gas formation to get the sections of clay content,clay lamination,porosity,fracture density,anisotropy parameters and uncertainty of the result.The estimated parameters can be used for better characterizations of shale gas reservoirs.In view of the complex mineral composition and microstructure of fractured shale reservoirs,we introduce a two-pore system model which combines the self-consistent effective media theory and Chapman’s model to account for the fractured shale.Considering the effects of shale compaction and fracture on anisotropy,an anisotropic shale rock physics model is constructed by combing the shale compaction model and Chapman’s model to simulate the anisotropy of shale accurately.As an extension of Bayesian theory,particle filter algorithm is a recursive Bayesian estimation method.Particle filter is applicable to nonlinear and non-Gaussian problems.It has been used in many fields,such as parameter estimation and target tracking.However,the algorithm is not very popular in geophysics.We present a shear wave velocity prediction method based on the rock physics model and particle filter.A particle filter system model for shale shear wave velocity prediction was established.The model was used in real well data,and analysis on algorithm improvement and parameter selection was made.Compared with the traditional method,particle filter has lower requirement for the accuracy of prior information,and better speed and accuracy.What’s more,the algorithm has potential to improve.Particle filter has also been used in anisotropy parameter inversion of shale.As a comparison,we first use the two-pore system model and the SA-PSO algorithm.In the inversion process,a smooth constraint is used to reduce the multiple solutions.Then,the inversion method of shale reservoir petrophysical parameters and anisotropic parameters based on rock physics model and particle filter is established.By using the prior information of unknown parameters,multiple solutions are avoided and the results become more accurate.These two methods are also used in the Longmaxi shale gas formation.The inversion result of reservoir petrophysical parameters and anisotropy parameters are consistent with former researches,which can provide abundant information for shale reservoir characterization.