The leaked contaminants from buried oil pipelines have a great potential to damage the ecological environment. It is significant to accurately and effectively predict the migration destination and diffusion range of oil contaminants in soil, which can keep contaminants to a minimum, and also can help to formulate the environmental impact assessment and remediation plan. In this paper, the Quartet Structure Generation Set algorithm (QSGS) is adopted to reconstruct the soil porous structure, and the binary image segmentation method is introduced to evaluate the algorithm quantitatively. The D2Q9 scheme of Lattice Boltzmann Method (LBM) is employed to simulate the mesoscopic scale migration of oil contaminants in soil. The influence of different porosities on the velocity field, pressure field and streamline distribution of oil contaminants in the computational domain is analyzed. Based on the measurement experiment of resistance coefficient in porous medium, the linear relationship between the square root of pressure difference Δp^0.5 and the percolation velocity v is obtained under four conditions. The migration resistance coefficient κ_R is introduced to characterize the migration ability of fluid in porous medium. When the contaminants type and permeation path length of fluid in porous medium are fixed, the migration resistance coefficient κ_R decreases with the increase of soil porosity, which can be described with a quadratic polynomial function. Thus, it is essential to investigate of pore-resistance relationship for the mesoscopic migration of oil contaminants in soil.

地下输油管道泄漏的污染物具有很大的破坏生态环境的潜力。准确有效地预测土壤中油类污染物的迁移目标和扩散范围具有重要意义，这可以使污染物含量降至最低，并有助于制定环境影响评估和修复计划。本文采用四方构造生成集算法（QSGS）重建土壤孔隙结构，并引入二值图像分割方法对该算法进行定量评价。采用格子Boltzmann方法（LBM）的D2Q9方案模拟土壤中油污染物的介观尺度迁移。不同孔隙度对速度场的影响，分析了计算域中的压力场和油污流线分布。基于多孔介质中阻力系数的测量实验，压差Δ的平方根之间呈线性关系p ^0.5和渗滤速度v在四个条件下获得。迁移阻力系数κ _{- [R}被引入来表征的流体在多孔介质中的迁移能力。当在多孔介质的流体中的污染物的类型和渗透路径长度是固定的，耐迁移性系数κ _{- [R}与土壤孔隙率的增加，其可以与一个二次多项式函数来描述降低。因此，研究孔隙-电阻关系对于土壤中油污染物的介观迁移至关重要。