图像处理算法在断层带微构造识别中的应用

Application of Image Processing Algorithm in Identification of Microstructures of Fault Zone

断层带相关微构造(裂缝、碎裂带等)的研究是刻画油气运移路径、提高注水开发效率的基础。由于微构造尺寸通常较小,导致常规分析测试方法无法准确测量其物性参数,因此为解决该问题提出了一种根据镜下图像进行物性计算的方法,首先将图像进行灰度转换和二值化处理,随后利用阿尔奇公式和改进的科泽尼-卡尔曼方程对样品的面孔率进行计算。除此以外,还采用了双线性插值算法对图形进行放大以捕捉到图像中更多细节。为了验证算法的准确性,以前人在野外收集到的碎裂岩样品的微观图像为对象进行运算。结果表明,双线性插值算法有助于捕捉原始图像的更多细节,有效地解决了直接放大后失真的问题,而且面孔率与渗透率的计算结果与实际分析测试结果误差较小,该算法能够准确计算微构造物性。

The study of the micro-structures associated with fault zones(fractures,cataclastic zones,etc.)is the basis for delineating the migration path of oil and gas and improving the efficiency of water injection development.Because the size of microstructures is usually small,the physical parameters cannot be accurately measured by conventional analytical methods.Therefore,this paper will use the image processing algorithm to calculate the physical properties of the image under the lens.Firstly,the image will be transformed into grayscale and binary.Then,the Archie formula and the improved Kozeny-Kalman equation are used to calculate the face rate of the sample.In addition,the bilinear interpolation algorithm is used to enlarge the graph to capture more details in the image.In order to verify the accuracy of the algorithm,the microscopic images of cataclastic rock samples collected by predecessors in the field are selected for calculation.The results show that the bilinear interpolation algorithm can help to capture more details of the original image,effectively solve the problem of direct magnification distortion.The error between the calculated results of face rate and permeability and the actual analysis test results is small,which proves this algorithm could calculate the microstructure accurately.