叠前反演结合地质统计模拟预测薄储层
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摘要
渤海湾盆地黄骅拗陷JD油田A构造区东一段的中浅层砂岩固结程度较差,砂岩与泥岩的纵波阻抗值域范围完全重合,地震资料分辨率极低(主频约为15Hz),利用叠后波阻抗反演及叠前反演很难实现薄储层预测及流体识别。文中利用Greenberg-Castagna模型进行叠前反演,结合地质统计模拟预测薄储层,具体研究思路为:首先,应用岩石物理建模技术得到每口井的纵、横波速度和密度曲线,生成储层流体属性曲线,并建立储层流体属性与岩性、流体之间的概率统计关系,从而得到每种岩性和流体的累积分布函数和概率密度分布函数;其次,应用横波预测结果进行井约束稀疏脉冲叠前同时反演,得到纵波阻抗、横波阻抗、密度、纵横波速度比、泊松比、拉梅系数等叠前弹性属性体,进一步生成储层流体属性数据体;然后,把储层流体属性数据体作为约束数据,依据每种岩性和流体与储层流体属性的统计关系,应用Monte-Carlo模拟方法进行地质统计模拟,最终得到研究区岩性模拟数据的多个实现。
In JD Oilfield of Bohai,China,delta fronts and distributary channel sands characterized by rapid lateral variations dominate reservoirs.Both extrusive(lava flow) and intrusive igneous rocks are distributed randomly in the target,and the resolution of seismic data is poor.Therefore it is difficult to predict reservoir with the thickness less than 15 m.Based on Greebert-castagna model,we propose a new approach for thin reservoir prediction by prestack inversion combined with geostatistic simulation.Through rock-physic modeling,a template for oil sands,oil-show sand,wet sands and non reservoir rocks in the area is established.A new attribute,which indicates variation of a sand reservoir and fluids in it,was found through elastic parameters combination.With this new attribute,we combined prestack inversion and geostatistcal simulation to make full use of both information to predict thin reservoir in the area and results are satisfied.
In JD Oilfield of Bohai,China,delta fronts and distributary channel sands characterized by rapid lateral variations dominate reservoirs.Both extrusive(lava flow) and intrusive igneous rocks are distributed randomly in the target,and the resolution of seismic data is poor.Therefore it is difficult to predict reservoir with the thickness less than 15 m.Based on Greebert-castagna model,we propose a new approach for thin reservoir prediction by prestack inversion combined with geostatistic simulation.Through rock-physic modeling,a template for oil sands,oil-show sand,wet sands and non reservoir rocks in the area is established.A new attribute,which indicates variation of a sand reservoir and fluids in it,was found through elastic parameters combination.With this new attribute,we combined prestack inversion and geostatistcal simulation to make full use of both information to predict thin reservoir in the area and results are satisfied.
引文
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[3]张军勇等.南堡滩海1234号构造精细解释、储层预测与目标优选(内部报告).东方地球物理公司,2009
[4]Greenberg M L and Castagna J P.Shear-wave velocityestimation in porous rocks;theoretical formulation,preliminary verification and applications.GeophysicalProspecting,1992,40(2):195～209
[5]Wang Xia et al.Application of Greenberg-Castagna modelin igneous rock region.SEG Technical Program Ex-panded Abstracts,2009,28:2233～2237
[6]王家映.蒙特卡洛法.工程地球物理学报,2007,4(2):81～85Wang Jia-ying.Monte Carlo Method.Chinese Journalof Engineering Geophysics,2007,4(2):81～85
[2]徐海滨,戴建春译.岩石物理手册.安徽合肥:中国科学技术大学出版社,2008
[3]张军勇等.南堡滩海1234号构造精细解释、储层预测与目标优选(内部报告).东方地球物理公司,2009
[4]Greenberg M L and Castagna J P.Shear-wave velocityestimation in porous rocks;theoretical formulation,preliminary verification and applications.GeophysicalProspecting,1992,40(2):195～209
[5]Wang Xia et al.Application of Greenberg-Castagna modelin igneous rock region.SEG Technical Program Ex-panded Abstracts,2009,28:2233～2237
[6]王家映.蒙特卡洛法.工程地球物理学报,2007,4(2):81～85Wang Jia-ying.Monte Carlo Method.Chinese Journalof Engineering Geophysics,2007,4(2):81～85
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