基于统计岩石物理的含气储层饱和度与孔隙度联合反演
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摘要
从地震数据中得到饱和度与孔隙度等储层物性参数是进行储层评价的关键。利用Gassmann方程讨论了储层岩石骨架特征、孔隙流体特征对介质地震弹性性质的影响,研究结果表明利用地震弹性属性反演饱和度等物性参数有其实现的特定岩石物理基础,其一是在气/水/油多相流体中,气体的体积模量相对于水/油的体积模量具有一定的可比性,而不能被忽略;其二是岩石骨架的纵波阻抗等弹性属性对所赋存孔隙流体的变化较为敏感。这样岩石的纵波阻抗等弹性参数随含水饱和度变化的变化率会明显增大,从而降低了从地震弹性属性中求取饱和度的不确定性和不稳定性。考虑到孔隙度与饱和度对储层岩石弹性特征影响的相关性,给出了基于随机岩石物理模型的Bayesian技术对孔隙度与含水饱和度进行联合反演的方法和步骤,并将该方法运用于高孔隙度含气砂岩储层的孔隙度及含水饱和度的预测中获得了较好的应用效果。
Extracting relatively accurate saturation value from seismic data was critical of pore fluid prediction and reservoir evaluation.The realization of saturation inversion had its rock physical basis,and depended on the elastic properties of pore fluid and the frame of reservoir rocks in different reservoir conditions.The bulk modulus of gas was comparable with that of brine and oil in the gas/oil/brine multi-phase system,it could not be neglected.Seismic elastic attributes,such as compressional impedance of rock frame was sensitive to the pore fluid variation.Under those conditions,the variation ratio of those elastic attributes,such as compressional impedance changing with water saturation was apparently raised,which could significantly reduce the ambiguity and instability of saturation inversion.Based on stochastic rock physical modeling,the joint inversion of saturation and porosity is realized by using Bayesian Inversion Method.This method is used to estimate water saturation and porosity for a high porosity gas reservoir and give a reliable estimation compared with drilling results.
Extracting relatively accurate saturation value from seismic data was critical of pore fluid prediction and reservoir evaluation.The realization of saturation inversion had its rock physical basis,and depended on the elastic properties of pore fluid and the frame of reservoir rocks in different reservoir conditions.The bulk modulus of gas was comparable with that of brine and oil in the gas/oil/brine multi-phase system,it could not be neglected.Seismic elastic attributes,such as compressional impedance of rock frame was sensitive to the pore fluid variation.Under those conditions,the variation ratio of those elastic attributes,such as compressional impedance changing with water saturation was apparently raised,which could significantly reduce the ambiguity and instability of saturation inversion.Based on stochastic rock physical modeling,the joint inversion of saturation and porosity is realized by using Bayesian Inversion Method.This method is used to estimate water saturation and porosity for a high porosity gas reservoir and give a reliable estimation compared with drilling results.
引文
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[4]Batzle M,Wang Z.Seismic properties of pore fluids[J].Geophysics,1992,57(6):1369～1408.
[5]Han De-Hua,Batzle M.Fizz water and lowgas saturated reservoirs[J].The Leading Edge,2002,22(2):395～398.
[6]Mavko G,Mukerji T,Dvorkin J.The rock physics handbook:tools for seismic analysis in porous media[M].New York:Cambridge University Press,1998.106～160.
[7]Duda R,Hart P,Stork D.Pattern classification[M].New York:John Wiley&Sons,2000.50～160.
[8]Hastings W.Monte Carlo sampling methods using Markov chains andits applications[J].Biometrika,1970,57(1):97～109.
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