School of Electrical Engineering, Xinjiang University
State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology

CO2地质封存是实现大量CO2减排的有效途径之一，而阐明CO2在岩石孔隙中的运移规律是CO2长期安全地质封存的关键。基于岩心微观结构重建的孔隙网络模型，不仅可以反映真实岩心孔喉分布规律，又能体现孔隙空间的分布及其发育特征，在多孔介质多相流研究领域具有十分重要的意义。选用储层较为常见的Berea砂岩，基于微焦点X射线计算机断层扫描(micro-CT)技术获得二维CT图像，在ImageJ软件中通过尺寸裁剪、降噪滤波以及阈值分割等一系列图像处理过程，重建了岩心样品数字图像，并在Matlab软件中借助提取函数实现了二值化；然后，采用最大球算法，通过搜索最大球、建立最大球连通关系、孔喉的识别和参数计算3个主要步骤，提取了实验岩心样品中的孔喉拓扑等效网络，并运用Amira软件进行可视化，将孔隙和吼道等效为球杆模型。通过对比不同图像处理与孔隙网络提取方法得到的岩心孔隙度、配位数、孔喉几何尺寸与形状因子等结构参数，确定了能够较好反映真实岩心孔隙空间特征的数字岩心重构及孔隙网络模型提取方法，即模型Pic7：滤波处理时将Mean值设置为1.5，Median值设置为2；阈值分割选择Otsu算法且应用最大球法提取数字岩心时将最小孔径设置为1。确定了Berea岩心孔隙结构参数：配位数分布在30以内，峰值在5左右；孔隙半径分布在80 μm内，集中在20 μm左右；吼道半径分布在60 μm内，集中在10 μm左右；孔隙形状因子和吼道形状因子分布在0.07以内，孔隙形状因子峰值在0.03左右，吼道形状因子峰值在0.035左右。最后，借助帝国理工大学开发的孔隙网络两相渗流模拟程序，用0.103 mol/kg NaCl溶液表征咸水，在50 ℃、12.4 MPa的储层条件下，开展了基于孔隙网络模型的多孔介质内CO2驱替咸水的渗流数值模拟，通过分析驱替和吸入过程中毛细管压力曲线和相对渗透率曲线，阐明了孔隙网络提取方法对多孔介质多相流过程的影响，再次验证了孔隙网络模型建模方法的可靠性以及所得建模参数的准确性。

It has been found in the recent studies that the CO2 geological storage is one of the efficient methods to achieve a large amount of CO2 reduction, while the understanding of the transport law of CO2 in the rock pore space is fundamental to the flexibility of a safe and long-term CO2 geological storage scheme. The pore network model based on the core micro-structure reconstruction can not only reflect the real core pore and throat distribution law, but also reflect the distribution of pore space and its development characteristics, which is of importance in the field of multi-phase flow research in porous media. The Berea sandstone, which is more common in the reservoir, was selected to obtain two-dimensional CT images based on the micro-focus X-ray computed tomography (micro-CT) technology, and the digital images of core samples were reconstructed in ImageJ software through a series of image processing processes such as size cropping, noise reduction filtering and threshold segmentation, and binarized in the Matlab software via extraction functions. Then, via the maximum sphere algorithm, the pore-throat topological equivalent network in the experimental core samples was extracted through three main steps, including searching the maximum sphere, establishing the maximum sphere connectivity, identification of pores and throats and parameter calculation, and visualized by using Amira software to equate the pores and throats to a spherical rod models. By comparing the structural parameters of core porosity, coordination number, pore and throat geometry and shape factor obtained via different image processing and pore network extraction methods, a digital core reconstruction and pore network model extraction method that can better reflect the spatial characteristics of real core pores was determined, such as model 7: the mean value is set to 1.5 and median value is set to 2 during filtering. The Otsu algorithm was selected for threshold segmentation and the minimum aperture was set to 1 when the digital core was extracted by the maximum sphere method. The pore structure parameters of Berea core were measured as follows: the coordination number was distributed within 30 and the peak value was around 5. The pore radius was distributed within 80 μm and concentrated around 20 μm. The throat radius was distributed within 60 μm and concentrated around 10 μm. The pore shape factor and throat shape factor were distributed within 0.07, the peak of pore shape factor was around 0.03, and the peak of throat shape factor was around 0.035. Finally, based on the pore network two-phase seepage simulation program developed by Imperial College of Technology, the seepage simulation of CO2-replaced brine in porous media was carried out under the reservoir conditions of 50 ℃ and 12.4 MPa by characterizing brine with 0.103 mol/kg NaCl solution. Then, the capillary pressure curve and relative permeability curve during the drainage and imbibition cycle were analyzed in detail. The influence of the pore network extraction method on the multi-phase flow process in porous media was elucidated, and the reliability of the pore network modeling method and the accuracy of the obtained modeling parameters were demonstrated again.

新疆维吾尔自治区自然科学基金青年基金资助项目(2021D01C089)；新疆维吾尔自治区重点研发资助项目(2022B01033-2)；中央引导地方科技发展专项资助项目(ZYYD2022C16)

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MEIHERIAYI Mutailipu，LI Tao，GU Wenbo，et al. Seepage characteristic of gas water based on pore network model[J]. Journal of China Coal Society，2023，48(7)：2802−2812.