改进分水岭算法在成像测井图砾石识别中的应用  

An Improved Watershed Algorithm and Its Application in Gravel Recognition of Imaging Logging

作　　者：刘文斌[1] 潘保芝[1] 张丽华[1] 栗猛[1] LIU Wenbin PAN Baozhi ZHANG Lihua LI Meng(College of Geoexploration Science and Technology, Jilin University, Changchun 130026, Jilin, China)

机构地区：[1]吉林大学地球探测科学与技术学院,吉林长春130026

出　　处：《西安石油大学学报（自然科学版）》2017年第1期89-94,126,共7页Journal of Xi’an Shiyou University（Natural Science Edition）

基　　金：国家科技重大专项"大型油气田及煤层气开发"(编号:2011ZX05044)

摘　　要：砾岩在成像图上显示的不规则性,导致其自动识别难度大、准确率低,而现行人工识别方法效率较低。为此,引入分水岭算法对成像测井图像砾岩中砾石识别进行探究,并通过添加滤波器、梯度处理以及感兴趣区域标记对算法进行改进,解决了基于拓扑理论和模拟地形学的分水岭算法所存在的过度分割问题。基于matlab软件将改进的分水岭算法应用到成像测井图像中,对W断陷A井成像测井资料进行处理,结果表明,该方法可识别出成像测井图像砾岩的大多数砾石,是一种成像测井中具有较高识别效率和准确率的砾岩自动识别方法。The irregularity of conglomerate on logging images makes the automatic identification of it difficult and inaccurate,and however the current manual identification method is of low efficiency. For this reason,the watershed algorithm is introduced to the conglomerate identification of electric imaging logging. The watershed algorithm is improved by adding filter,gradient processing and interested region marking,which solves the problem of the over segmentation of the watershed algorithm based on topology theory and simulated topography. Based on matlab,the improved watershed algorithm is applied to the identification of the gravel in logging image. The processing result of the imaging logging data of well A in W fault depression shows that,the most of gravels in the conglomerate logging image can be identified using the improved watershed algorithm,and the method is an automatic recognition method of conglomerate with high recognition efficiency and accuracy in imaging logging.

关 键 词：成像测井 砾石识别 图像处理 改进分水岭算法 

分 类 号：TE319[石油与天然气工程—油气田开发工程]