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分形维数在复杂碳酸盐岩储集空间类型分析中的应用——以靖西地区马家沟组中组合为例
The Application of Fractal Dimension in Analysis of Complex Carbonate Reservoir Space Type—A Case of the Middle Array of Majiagou Formation of Jingxi Area

DOI: 10.12677/AG.2021.119109, PP. 1131-1140

Keywords: 碳酸盐岩储层,分形维数,储集空间类型,成像测井,靖西地区
Carbonate Reservoir
, Fractal Dimension, Reservoir Space Type, Imaging Logging, Jingxi Area

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Abstract:

碳酸盐岩储集空间类型评价对于碳酸盐岩储层勘探开发具有重要指导作用。靖西地区马家沟组中组合碳酸盐岩储层储集空间可划分为溶蚀孔(洞)、晶间孔和裂缝三种类型。三类储集空间类型的毛管压力曲线形态具有明显的类别区分特征。计算了25块岩心样品毛管压力曲线的分形维数,发现分形维数对三类储层具有明显的可区分性。由于毛管压力曲线和核磁共振测井资料均反映储层微观孔隙结构特征,但工区核磁共振测井资料相对较少,而电成像测井资料丰富,因此,从电成像测井资料中提取视孔隙度谱,并把视孔隙度谱转化为类似核磁共振T2谱特征曲线,采用计算核磁共振T2谱分形维数的方法,计算电成像资料的分形维数,并把这一分形维数用于靖西地区马家沟组中组合碳酸盐岩储集空间类型的划分。应用效果表明,利用电成像资料获得的分形维数,可以作为储集空间类型划分的重要参数。
The evaluation of carbonate reservoir space type plays an important role in the exploration and development of carbonate reservoir. The reservoir space of carbonate reservoirs in the middle array of Majiagou formation in Jingxi area can be divided into three types: dissolved pores (caves), intercrystalline pores and fractures. The capillary pressure curves of the three types of reservoir space have obvious characteristics of classification. The fractal dimension of capillary pressure curves of 25 core samples is calculated, and it is found that the fractal dimension can distinguish three types of reservoirs. Because the capillary pressure curve and NMR logging data both reflect the microscopic pore structure characteristics of the reservoir, but the NMR logging data in the working area are relatively few, and the electrical imaging logging data are abundant, therefore, the apparent porosity spectrum is extracted from electrical imaging logging data and converted into similar NMR T2 spectrum characteristic curve. The fractal dimension of electrical imaging data is calculated by calculating the fractal dimension of NMR T2 spectrum, the fractal dimension is applied to the classification of the carbonate reservoir space types in the middle array of Majiagou formation in the Jingxi area. The application results show that the fractal dimension obtained from electrical imaging data can be used as an important parameter for the classification of reservoir space.

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