用多尺度形态学方法实现成像测井电导率图像的缝洞参数表征

发布时间：2018-06-14 17:06

本文选题：微电扫描成像测井 + 多尺度形态学滤波　；参考：《中国石油大学学报(自然科学版)》2017年01期

【摘要】：裂缝和溶蚀孔洞为缝洞型储层提供了主要的储集空间和渗流通道,其分布的随机性和复杂性严重影响了对缝洞储层的定量评价。基于高覆盖率和高分辨率的电成像测井数据,采用多尺度数学形态学方法提取电导率图像中的缝洞孔隙度谱。选择不同尺度和形状的结构元素,构造不同种类的形态学滤波算子,实现井壁裂缝和溶蚀孔洞的电导率异常边缘检测。针对缝洞异常的边缘检测结果,用椭圆形函数拟合溶蚀孔洞,用多项式插值函数拟合裂缝边缘,继而提取缝洞参数并获得缝洞孔隙度谱。实验结果表明,用多尺度数学形态学方法对电导率图像的边缘检测有效地实现了缝洞的自动识别,验证了该方法计算缝洞孔隙度谱的准确性。
[Abstract]:Fractures and dissolution pores provide the main reservoir space and percolation channel for the fracture-cavity reservoir, and the randomness and complexity of the distribution seriously affect the quantitative evaluation of the fracture-cavity reservoir. Based on the electrical imaging logging data with high coverage and high resolution, the porosity spectrum of fracture and cavity in conductivity image is extracted by multi-scale mathematical morphology method. Different morphological filter operators are constructed by selecting structural elements of different scales and shapes to detect abnormal conductivity edge of fracture and solution hole in wellbore. The elliptical function is used to fit the solution hole and the polynomial interpolation function is used to fit the crack edge, and then the fracture cavity parameters are extracted and the porosity spectrum is obtained. The experimental results show that the multi-scale mathematical morphology method is used to detect the edge of conductivity image effectively and the accuracy of calculating the porosity spectrum of fracture and cavity is verified.
【作者单位】：中国石油大学地球物理与信息工程学院;中国石油集团华北油田测井有限公司;
【基金】：中国石油天然气股份有限公司重大科技专项(2014E-35)
【分类号】：P618.13;P631.811

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