基于统计岩石物理模型的各向异性页岩储层参数反演

Probabilistic reservoir parameters inversion for anisotropic shale using a statistical rock physics model

提出了各向异性页岩储层统计岩石物理反演方法.通过统计岩石物理模型建立储层物性参数与弹性参数的定量关系,使用测井数据及井中岩石物理反演结果作为先验信息,将地震阻抗数据定量解释为储层物性参数、各向异性参数的空间分布.反演过程在贝叶斯框架下求得储层参数的后验概率密度函数,并从中得到参数的最优估计值及其不确定性的定量描述.在此过程中综合考虑了岩石物理模型对复杂地下介质的描述偏差和地震数据中噪声对反演不确定性的影响.在求取最大后验概率过程中使用模拟退火优化粒子群算法以提高收敛速度和计算准确性.将统计岩石物理技术应用于龙马溪组页岩气储层,得到储层泥质含量、压实指数、孔隙度、裂缝密度等物性,以及各向异性参数的空间分布及相应的不确定性估计,为页岩气储层的定量描述提供依据.

A stochastic inversion method of reservoir parameters for anisotropic shale is proposed by combing a rock physics model and Bayesian estimation.Quantitative relations between elastic parameters such as P-and S-wave impedances and reservoir petrophysical parameters including fracture and porosity are investigated using a statistical rock physics model.During the modeling,the error of rock physics model and noises in the seismic data are considered.In the process of estimating reservoir petrophysical parameters from elastic parameters,Bayesian inversion based on the statistical rockphysics model is applicable to the uncertainty problem by giving the posterior probability distribution（PDF）of the unknown parameters.Then reservoir properties are obtained by the maximum a posteriori（MAP）criteria and associated uncertainty analysis.In the stochastic inversion,the SA-PSO algorithm which combines the simulated annealing method and the particle swarm optimization method shows its advantages in accuracy and efficiency.This method is applied to the Longmaxi Formation shale in China to obtain the sections of clay lamination（CL）,clay content,porosity,fracture density and anisotropy parameters from given seismic sections of P-and S-wave impedances.The estimated reservoir parameters can be used for better characterizations of the sweet spots in shale reservoirs.