基于逾渗网络模型和升尺度方法的储层岩石电性研究
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摘要
为了解决复杂储层测井精细解释与评价中遇到的潜在困难,必须开展有针对性的岩石物理基础研究。电阻率参数在储层识别、饱和度定量评价等中具有极其重要的作用,但目前对储层岩石电性影响因素及规律的认识还不完善。为此,本文首先建立了能够反映储层微观孔隙结构、流体性质、孔隙—流体之间相互作用等特征的逾渗网络模型,通过数值模拟研究了岩石电性的微观影响因素及规律,然后创新性地将升尺度方法用于储层宏观特性对岩石电性影响规律的研究之中,最后通过理论分析获得了具有物理意义及通用性的MESPG导电模型。
在建立逾渗网络模型时充分考虑了孔隙尺寸大小、均匀性、相关性、孔隙之间的连通性、润湿性、矿化度以及分散泥质等储层特征。通过微观模拟,讨论了上述微观因素对岩石电性的影响及规律。通过最优化拟合,定量研究了几个重要的储层孔隙结构特征对电性影响的相对强度。根据实际资料,考察了低孔低渗储层、高孔高渗储层、低阻储层电性的微观影响规律。在升尺度处理时根据不同的宏观特性,采用了不同的升尺度方法:基于混合理论的结构泥质升尺度处理;基于DBU方法的层状泥质升尺度处理;物性渐变储层的基于毛细管压力的升尺度处理;裂缝的体积平均升尺度处理方法。
模拟研究发现,孔隙度同饱和度指数之间并非通常文献所述的简单线性关系,而与润湿性、孔喉比等特性有关。相对于孔隙尺寸大小而言,孔隙尺寸的空间分布对岩石电性的影响更为显著。定量拟合研究表明,孔隙连通性、微孔隙对岩石电性的影响非常显著,且易产生非阿尔奇特性,而孔隙尺寸和形状的影响较弱。相对于高孔高渗储层而言,地层水电阻率、泥质含量等对低孔低渗储层电性具有显著的影响。理论和模拟研究均表明在水湿储层中I ? Sw曲线可呈现“凹型”、“凸型”非阿尔奇特性,具体形状同连通状况、均质性等有关。首次通过微观模拟证实了泥质的多重作用,并获得了泥质从减阻作用转化为增阻作用的临界矿化度同孔隙度、渗透率等储层特性之间的定性关系。除泥质自身特性外,泥质分布形式对岩石电性具有显著的影响,不同泥质应采用不同的升尺度方法。在不同影响因素下, I ? Sw曲线可呈现不同的形状,但均可归结于三种典型的形状。实例分析表明MESPG导电模型具有通用性、物理意义明显且满足理论边界。
In order to resolve the problems facing in the well log fine interpretation and the evaluation of the complex reservoir, it is important to take the corresponding basic petrophysical researches. The rock resistivity is one of the important parameters in reservoir identification, saturation evaluation et al., but it is not perfection in the understanding of the influencing factors and laws of rock resistivity. Therefore, in this thesis the percolation network model that can describe the microcosmic pore structure of the reservoir rock, fluid properties and interaction between fluids and pores, is firstly built. Then the microcosmic influencing factors and laws of rock resistivity are discussed through numerical modeling. Upscaling methods are innovatively used to study the macroscopical influencing factors and laws of rock resistivity. At last, based on theoretical analysis, the MESPG conductivity model is built, which has physical meaning and is universal.
The reservoirs rock microcosmic characteristics, such as pore size, uniformity, correlation, connectivity of the pores, wettability, fluid salinity, dispersed shale and so on, are considered in building percolation network model. Through microcosmic modeling, the effects of the characteristics mentioned above on rock resistivity are discussed in detail. Through optimal fitting, the influencing magnitude of several pore structure parameters on rock reisitivity is studied. Based on actual oilfield data, the influencing laws of the rock microcosmic characteristics on resisitivity in low porosity and permeability reservoir, high porosity and permeability reservoir and in low resistivity reservoir are discussed. During upscaling, the different methods are adopted for different macroscopical reservoir characteristics: the upscaling method based on mixture theory for the structure shale, the upscaling method based on the DBU for laminated shale, the upscaling method based on the capillary pressure for the reservoir with property gradual changing, the upscaling method based on the volume average for fractured reservoir.
The modeling results indicate that there is not simple linear relation between saturation exponent and porosity described in some literatures. The relation between saturation exponent and porosity also depends on the wettability, pore-throat ratio and so on. The distribution of the pores has greater effect on rock resisitivity than the pore size. The fitting results show that pore connectivity and the micropores have great effect on rock resistivity and these factors easily lead to non-Archie phenomenon. However, the pore size and the pore shape have little effect. The formation water salinity and the shale have greater effect on rock resistivity in low porosity and low permeability reservoir than that in high porosity and high permeability reservoir. Both theoretical and modeling results show that the I-Sw curve in water wetting reservoir can represent convexity or concave shapes. The actual shape of the I-Sw curve depends on the pore connectivity, uniformity and so on. Throughing microcosmic modeling, we confirm the multi-role of the shale and gain the qualitative relation between the critical salinity in which shale pole changes from reducing resistivity to increasing resistivity role, and the reservoir characteristics such as porosity, permeability. Besides itself properties of the shale, the shale content and shale distribution form have great effect on rock resistivity. Different upscaling methods should been used for different shale distribution forms. For different reservoir rocks, the different I-Sw curve shapes can be appeared, but all shapes can be reduced to three representative types. The analysis results of experimental data show that the MESPG conductivity model is universal, has physical meaning and satisfies theoretical boundary.
在建立逾渗网络模型时充分考虑了孔隙尺寸大小、均匀性、相关性、孔隙之间的连通性、润湿性、矿化度以及分散泥质等储层特征。通过微观模拟,讨论了上述微观因素对岩石电性的影响及规律。通过最优化拟合,定量研究了几个重要的储层孔隙结构特征对电性影响的相对强度。根据实际资料,考察了低孔低渗储层、高孔高渗储层、低阻储层电性的微观影响规律。在升尺度处理时根据不同的宏观特性,采用了不同的升尺度方法:基于混合理论的结构泥质升尺度处理;基于DBU方法的层状泥质升尺度处理;物性渐变储层的基于毛细管压力的升尺度处理;裂缝的体积平均升尺度处理方法。
模拟研究发现,孔隙度同饱和度指数之间并非通常文献所述的简单线性关系,而与润湿性、孔喉比等特性有关。相对于孔隙尺寸大小而言,孔隙尺寸的空间分布对岩石电性的影响更为显著。定量拟合研究表明,孔隙连通性、微孔隙对岩石电性的影响非常显著,且易产生非阿尔奇特性,而孔隙尺寸和形状的影响较弱。相对于高孔高渗储层而言,地层水电阻率、泥质含量等对低孔低渗储层电性具有显著的影响。理论和模拟研究均表明在水湿储层中I ? Sw曲线可呈现“凹型”、“凸型”非阿尔奇特性,具体形状同连通状况、均质性等有关。首次通过微观模拟证实了泥质的多重作用,并获得了泥质从减阻作用转化为增阻作用的临界矿化度同孔隙度、渗透率等储层特性之间的定性关系。除泥质自身特性外,泥质分布形式对岩石电性具有显著的影响,不同泥质应采用不同的升尺度方法。在不同影响因素下, I ? Sw曲线可呈现不同的形状,但均可归结于三种典型的形状。实例分析表明MESPG导电模型具有通用性、物理意义明显且满足理论边界。
In order to resolve the problems facing in the well log fine interpretation and the evaluation of the complex reservoir, it is important to take the corresponding basic petrophysical researches. The rock resistivity is one of the important parameters in reservoir identification, saturation evaluation et al., but it is not perfection in the understanding of the influencing factors and laws of rock resistivity. Therefore, in this thesis the percolation network model that can describe the microcosmic pore structure of the reservoir rock, fluid properties and interaction between fluids and pores, is firstly built. Then the microcosmic influencing factors and laws of rock resistivity are discussed through numerical modeling. Upscaling methods are innovatively used to study the macroscopical influencing factors and laws of rock resistivity. At last, based on theoretical analysis, the MESPG conductivity model is built, which has physical meaning and is universal.
The reservoirs rock microcosmic characteristics, such as pore size, uniformity, correlation, connectivity of the pores, wettability, fluid salinity, dispersed shale and so on, are considered in building percolation network model. Through microcosmic modeling, the effects of the characteristics mentioned above on rock resistivity are discussed in detail. Through optimal fitting, the influencing magnitude of several pore structure parameters on rock reisitivity is studied. Based on actual oilfield data, the influencing laws of the rock microcosmic characteristics on resisitivity in low porosity and permeability reservoir, high porosity and permeability reservoir and in low resistivity reservoir are discussed. During upscaling, the different methods are adopted for different macroscopical reservoir characteristics: the upscaling method based on mixture theory for the structure shale, the upscaling method based on the DBU for laminated shale, the upscaling method based on the capillary pressure for the reservoir with property gradual changing, the upscaling method based on the volume average for fractured reservoir.
The modeling results indicate that there is not simple linear relation between saturation exponent and porosity described in some literatures. The relation between saturation exponent and porosity also depends on the wettability, pore-throat ratio and so on. The distribution of the pores has greater effect on rock resisitivity than the pore size. The fitting results show that pore connectivity and the micropores have great effect on rock resistivity and these factors easily lead to non-Archie phenomenon. However, the pore size and the pore shape have little effect. The formation water salinity and the shale have greater effect on rock resistivity in low porosity and low permeability reservoir than that in high porosity and high permeability reservoir. Both theoretical and modeling results show that the I-Sw curve in water wetting reservoir can represent convexity or concave shapes. The actual shape of the I-Sw curve depends on the pore connectivity, uniformity and so on. Throughing microcosmic modeling, we confirm the multi-role of the shale and gain the qualitative relation between the critical salinity in which shale pole changes from reducing resistivity to increasing resistivity role, and the reservoir characteristics such as porosity, permeability. Besides itself properties of the shale, the shale content and shale distribution form have great effect on rock resistivity. Different upscaling methods should been used for different shale distribution forms. For different reservoir rocks, the different I-Sw curve shapes can be appeared, but all shapes can be reduced to three representative types. The analysis results of experimental data show that the MESPG conductivity model is universal, has physical meaning and satisfies theoretical boundary.
引文
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