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戚明辉, 李君军, 曹茜. 基于扫描电镜和JMicroVision图像分析软件的泥页岩孔隙结构表征研究[J]. 岩矿测试, 2019, 38(3): 260-269. DOI: 10.15898/j.cnki.11-2131/td.201901160008
引用本文: 戚明辉, 李君军, 曹茜. 基于扫描电镜和JMicroVision图像分析软件的泥页岩孔隙结构表征研究[J]. 岩矿测试, 2019, 38(3): 260-269. DOI: 10.15898/j.cnki.11-2131/td.201901160008
Ming-hui QI, Jun-jun LI, Qian CAO. The Pore Structure Characterization of Shale Based on Scanning Electron Microscopy and JMicroVision[J]. Rock and Mineral Analysis, 2019, 38(3): 260-269. DOI: 10.15898/j.cnki.11-2131/td.201901160008
Citation: Ming-hui QI, Jun-jun LI, Qian CAO. The Pore Structure Characterization of Shale Based on Scanning Electron Microscopy and JMicroVision[J]. Rock and Mineral Analysis, 2019, 38(3): 260-269. DOI: 10.15898/j.cnki.11-2131/td.201901160008

基于扫描电镜和JMicroVision图像分析软件的泥页岩孔隙结构表征研究

The Pore Structure Characterization of Shale Based on Scanning Electron Microscopy and JMicroVision

  • 摘要: 孔隙发育特征是泥页岩储集能力评价的关键参数之一。扫描电镜观察法已普遍用于描述泥页岩的孔隙发育特征,但是目前文献中对泥页岩微孔隙类型划分比较混乱,孔隙结构特征参数的表征以定性描述为主,缺乏定量表征手段。本文选取了18个泥页岩样品为研究对象,通过氩离子抛光和高分辨率扫描电子显微镜图像观察,基于孔隙发育形态、位置及成因,对样品中不同孔隙进行类型划分;结合JMicroVision图像分析软件,应用泥页岩微孔隙描述技术和孔隙尺度分类统计技术,统计不同类型孔隙发育数量、孔径大小、面孔率、形状系数、概率熵等参数,对其分布特征进行评价。研究表明,晶(粒)间孔隙和有机孔隙比较发育,其次为晶(粒)内孔和晶间隙。不同类型孔隙其孔径分布以纳米级为主,不同类型孔隙分布较无序,其概率熵主要分布在0.5~0.7之间,对应的形状系数分布差异也较大。有机质孔隙的形状系数主要分布在0.6~0.7范围内,形状分布以椭圆形或近似圆形为主,晶(粒)间孔隙和晶(粒)内孔隙的形状系数主要分布在0.3~0.7,分析晶(粒)间孔隙和晶(粒)内孔隙形状系数分布特征主要是受原始孔隙形态、压实作用和溶蚀作用的影响。研究认为,SEM与JMicroVision相结合是定量研究不同类型微孔发育特征的有效手段,为研究微孔的形成和演化奠定了基础。

     

    Abstract:
    BACKGROUNDThe pore characteristics of shale are one of the key parameters for evaluation of the shale reservoir capacity. Scanning Electron Microscopy (SEM) has been widely used to describe the pore characteristics of shale. However, the classification of micro-pore types in mud shale reservoirs in the literature was relatively diverse, and the quantitative characterization of pore based on SEM was relatively lacking.
    OBJECTIVESTo classify the pore types and quantitatively characterize these pores in shale.
    METHODS18 shale samples were selected as the research object in this study. Based on the form, position and origin of pores observed by argon ion polishing and Scanning Electron Microscopy, the types of different pores in the sample were classified. By using JMicroVision image analysis software, the pore characteristics including the number of pore types, pore size, face rate, shape coefficient, probability entropy and other parameters were quantitatively described.
    RESULTSThe inter-crystal (particle) pores and organic pores were the most developed, followed by intra-crystal (particle) pores and crystal gap inter-crystal (particle) pores. The sizes of pore were mainly nanometer. The probabilistic entropy of intra-crystal (particle) pores and organic pores were mainly distributed between 0.5 and 0.7, with a different shape coefficient distribution. The shape coefficients of organic pores were mainly distributed between 0.6 and 0.7, and their shape were mainly oval or nearly circular. The shape coefficient of intra-crystal (particle) pores and inter-crystal (particle) pores were mainly between 0.3 and 0.7, which were mainly affected by the original pore morphology, compaction and dissolution.
    CONCLUSIONSThe combination of SEM and JMicroVision is an effective means to quantitatively study the development characteristics of different types of micropores. This work has laid a foundation for the study of the genesis and evolution of micropores.

     

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