基于数字岩心分形特征的渗透率预测方法

doi:10.13278/j.cnki.jjuese.20190148

摘要/Abstract

摘要： 基于数字岩心技术，对岩心CT扫描图像进行处理，结合分形理论求取数字岩心的分形特征参数并通过构建数字岩心的等效分形介质模型对岩心渗透率进行预测。首先对两块砂岩岩心进行了微米CT扫描，提取岩心孔隙网络模型，分析岩心孔隙结构特征，结果表明岩心的孔喉半径分布与孔喉配位数分布对岩心渗透率有一定影响；其次利用MATLAB、Image J等软件对CT扫描得到的数字岩心及帝国理工学院网站公开的数字岩心进行处理，基于分形理论求取数字岩心分形维数、迂曲度、迂曲度分形维数和最大孔隙直径等参数；最后基于分形渗透率模型对岩心渗透率进行预测。结果表明：预测渗透率与岩心渗透率具有良好的相关性，相关系数大于0.97。因此，基于数字岩心技术，通过构建数字岩心等效分形介质模型，可以有效预测岩心渗透率。

关键词: 数字岩心, CT扫描, 渗透率, 分形, 孔隙结构

Abstract: Based on digital rock technology, the core CT scanning images are processed to obtain the core fractal parameters with fractal theory, and then the core permeability is predicted by constructing an equivalent fractal model of digital rock. In this study, firstly, the micro-CT scanning experiments of two sandstones were carried out,the core pore network models were extracted, and the pore throat structures were analyzed. Further, these two digital rocks and nine digital rocks from the Imperial College were processed to obtain the fractal parameters including fractal dimension, tortuosity, tortuosity dimension, and maximum pore radius by using MATLAB and Image J. Finally, based on the fractal permeability model, the permeability of cores was predicted. The results show that the pore throat radius distribution and pore coordination number distribution have influence on core permeability. The predicted permeability has a good correlation with the core permeability, and the correlation coefficient is greater than 0.97. Therefore, the core permeability can be effectively predicted based on digital rock technology by constructing an equivalent fractal model.

Key words: digital rock, CT scanning, permeability, fractal, pore structure

中图分类号:

TE311

杨坤, 王付勇, 曾繁超, 赵久玉, 王聪乐. 基于数字岩心分形特征的渗透率预测方法[J]. 吉林大学学报(地球科学版), 2020, 50(4): 1003-1011.

Yang Kun, Wang Fuyong, Zeng Fanchao, Zhao Jiuyu, Wang Congle. Permeability Prediction Based on Fractal Characteristics of Digital Rock[J]. Journal of Jilin University(Earth Science Edition), 2020, 50(4): 1003-1011.

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