基于骨架网络模型的岩石粒径分析方法

应用扫描电子显微镜,获取岩石的二维灰度图像,并进一步分割得到岩石的骨架和孔喉结构。利用马尔可夫链蒙特卡洛法构建三维数字岩心,提取相应的三维孔隙网络模型。根据其逆过程提出骨架网络模型的提取方法,可对岩石粒径进行定量分析。最后对三块低渗透岩心样品的颗粒半径、孔隙半径和喉道半径等结构参数进行对比分析,得到各样品结构参数之间的定量关系。研究表明,基于网络模型的岩石粒径分析法能够快速获取岩石的结构参数,对油藏岩石结构参数进行定量表征,大大缩短实验数据获取周期,为岩石结构参数分析提供了一套有效的研究思路。

A Method for Rock Particle Size Analysis Based on Skeleton Network Model

Based on Scanning Electron Microscope (SEM), the 2D binary images are obtained and the segmentation algorithm is used to distinguish rock skeleton and pore structure; then, Markov Chain Monte Carlo (MCMC) method is used to reconstruct 3D digital rock, and the corresponding 3D pore network model are extracted, the extraction method of 3D skeleton network model is proposed based on the inverse process and the rock particle size could be analyzed quantitatively; at last, three low permeability rock samples are taken as the example to analyze the structure parameters including particle radius, pore radius and throat radius, and the relationship among the rock structure parameters are described quantitatively. Results show that, the new method for rock particle size analysis based on network model acquires the rock structure parameters quickly, and characterizes the structure parameters quantitatively, which could shorten the data collection time and provide an effective research idea for rock structure parameters analysis.