State Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology, Xuzhou 221116, China.
School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221116, China.
Phys Rev E. 2019 Nov;100(5-1):053314. doi: 10.1103/PhysRevE.100.053314.
Pore size distribution (PSD), which is defined as the percentage of the pores of each size to the total volume of the pores, is a key parameter to characterize the microstructure of porous media. Based on the pore geometry definition of three-dimensional (3D) maximal ball and two-dimensional (2D) maximal disk in discrete space, an improved algorithm is proposed to obtain PSD from pore space images of porous media. To validate the accuracy of our algorithm, a synthetic porous medium with a known PSD is generated by computer simulation. In addition, other 2D and 3D images of various types of samples, including sandstones, carbonates, and man-made materials, were also used to obtain PSD. The PSDs were compared quantitatively with that obtained by using the existing state of the art algorithm. The results show that our algorithm is more accurate in characterizing the pore structure and more consistent with the direct visual identification. In addition, the efficiency of our algorithm was also evaluated by calculating the PSD of large-scale 3D images, the results of which indicate that all calculations can be completed in a relatively short time.
孔径分布（PSD）定义为每个孔径尺寸的孔体积占总孔体积的百分比，是描述多孔介质微观结构的关键参数。基于离散空间中三维（3D）最大球和二维（2D）最大圆盘的孔几何定义，提出了一种改进的算法，从多孔介质的孔空间图像中获取 PSD。为了验证我们算法的准确性，通过计算机模拟生成了具有已知 PSD 的合成多孔介质。此外，还使用各种类型的样品（包括砂岩、碳酸盐岩和人造材料）的其他 2D 和 3D 图像来获取 PSD。将 PSD 与使用现有最先进算法获得的 PSD 进行定量比较。结果表明，我们的算法在描述孔结构方面更加准确，并且与直接目视识别更加一致。此外，还通过计算大规模 3D 图像的 PSD 来评估我们算法的效率，结果表明所有计算都可以在相对较短的时间内完成。
