基于随机地震反演的Russell流体因子直接估算方法  

A direct estimation method for the Russell fluid factor based on stochastic seismic inversion

作　　者：孙瑞莹 印兴耀[1] 王保丽[1] 张广智[1] 

机构地区：[1]中国石油大学(华东)地球科学与技术学院,山东青岛266580

出　　处：《地球物理学报》2016年第3期1143-1150,共8页Chinese Journal of Geophysics

基　　金：国家重点基础研究发展计划(973计划)(2013CB228604);国家科技重大专项(2011ZX05009);山东省自然科学基金(ZR2011DQ013);国家自然科学基金(41204085)联合资助

摘　　要：本文研究了一种基于随机地震反演的Russell流体因子直接估算方法,该方法是一种基于蒙特卡罗的非线性反演,能够有效地融合测井资料中的高频信息,提高反演结果的分辨率.本文应用贝叶斯理论框架,首先通过测井数据计算井位置处的Russell流体因子,利用序贯高斯模拟方法(sequential Gaussian simulation,SGS)得到流体因子的先验信息;然后构建似然函数;最后利用Metropolis抽样算法对后验概率密度进行抽样,得到反演的Russell流体因子.其中对每道数据进行序贯高斯模拟时,采用一种新的逐点模拟方式,具有较高的计算速度.数值试验表明:反演结果与理论模型和实际测井数据吻合较好,具有较高的分辨率,对于判识储层含流体特征具有较好的指示作用.Most fluid factors are based on single-phase medium theory.However,the rockphysics based on two-phase medium theory can better study the effects of pore fluid on the elastic properties of rock medium.The Russell fluid factor is the most commonly used two-phase fluid factor.It has higher fluid sensitivity for which the consolidation is mature and the porosity change is relatively small.And stochastic seismic inversion can simulate the information from the seismic frequency range with spatial constraints of the well-logging data.Its resolution is higher than that of conventional deterministic inversion method.In this paper we propose a direct estimation method for the Russell fluid factor based on stochastic seismic inversion.It is a Monte Carlo based strategy for non-linear inversion,which can effectively integrate the high-frequency information of well-logging data and have a higher resolution.The method is formulated in the Bayesian framework.Firstly,we calculate the Russell fluid factor using welllogging data and get the priori information of fluid factor through the improved sequential Gaussian simulation（SGS）.Then we construct the likelihood function combining high-frequency priori constraints based on geostatistics and low-frequency constraints commonly used indeterministic inversion,which overcomes the frequency missing problem caused by band-limited properties of the wavelet.When calculating synthetic seismogram we use the exact Zoeppritz equation which can reduce the errors caused by Zoeppritz equation approximations.Here,we define the priori information and likelihood function as Gaussian probability density.As a consequence of nonlinearity,no closed form expression of the posteriori probability density can be formulated.Therefore,we apply the Metropolis algorithm to obtain an exhaustive description of the posteriori probability density.Although the stochastic seismic inversion method can effectively integrate high-frequency information of well-logging data,however,it has low computation efficiency a

关 键 词：序贯高斯模拟 贝叶斯理论 Russell流体因子 高分辨率 随机地震反演 

分 类 号：P631[天文地球—地质矿产勘探]