基于砂岩数字岩芯图像的渗透率模拟与粗化

运用闵可夫斯基泛函,结合K-means聚类方法,对应用CT扫描获得的砂岩数字岩芯图像进行岩石类型的精细划分,将岩芯划分成为粗粒区、细粒区和过渡区,进而获得岩芯的精细分层。基于砂岩数字岩芯图像,应用岩芯驱替模拟变换法,模拟在不同驱替压力条件下岩芯中湿相与非湿相的分布状况。应用格子玻尔兹曼方法(LBM),对岩芯各个小层进行渗透率的计算模拟,并采用直接加权平均、回归各岩石类型孔-渗关系曲线以及去除薄层后回归各岩石类型孔-渗关系曲线3种方法,完成对岩芯渗透率参数的粗化,获得粗化后的渗透率参数和孔-渗关系曲线方程。

Research of Permeability Numerical Prediction and Upscaling Based on Micro-CT Computed Tomography of Sandstone Core Sample

Digital core analysis based on micro-CT computed tomography provide a new approach in core samples' permeability numerical prediction. Firstly, Minkowski functionals is applied along with theK-means cluster analysis to separate the sandstone core sample gotten from the micro-CT computed tomography into distinct classes, well-sorted fine grain, well-sorted large grain and transition area in order to get the elaborate layer system. Secondly, capillary drainage transform is performed to simulate the distribution of wetting and non-wetting phases under different drainage pressures. Lastly, LBM method is operated based on the core layer system to model permeability of each layers and upscaling is applied based on the simulated results with 3 different ways: directly applying the average method on the prediction values, finding the correlation function of permeability and porosity with and without thin layers in order to get the upscaling values of permeability and correlation function of permeability and porosity.