基于Beamlet变换的数字地质露头裂缝线性特征提取  

LINEAR FEATURE EXTRACTION OF DIGITAL GEOLOGICAL OUTCROP CRACK BASED ON BEAMLET TRANSFORM

作　　者：付含聪 邓帆 曾齐红[2] 邵燕林[1] Fu Hancong;Deng Fan;Zeng Qihong;Shao Yanlin(School of Geosciences,Yangtze University,Wuhan 430100,Hubei,China;Research Institute of Petroleum Exploration&Development,Beijing 100083,China)

机构地区：[1]长江大学地球科学学院,湖北武汉430100 [2]中国石油勘探开发研究院,北京100083

出　　处：《计算机应用与软件》2022年第10期198-202,291,共6页Computer Applications and Software

基　　金：国家科技重大专项(2017ZX05001001);湖北省高等学校实验室研究项目(HBSY2018-28)。

摘　　要：裂缝识别与表征是裂缝性油气藏研究的重要内容,为了实现对数字地质露头裂缝线性特征的自动提取及精确描述,设计一种基于多尺度Beamlet变换的数字地质露头裂缝提取方法。利用多尺度自适应增强算法对灰度图像进行增强处理以减弱背景噪声和光照不均的干扰,利用大津阈值法分割裂缝和背景得到裂缝二值图像;对二值图像进行Beamlet变换得到裂缝线性特征;对离散裂缝线段进行连接。实验结果表明,与Canny边缘检测算法和Hough变换算法相比,该方法具有更好的抗噪能力,提取的裂缝线性特征更准确、完整。通过采用自适应增强处理和离散线段连接算法减少了光照不均和线段不连通等问题,充分发挥了Beamlet算法在线性特征提取方面的优势。Crack identification and characterization is an important part of fractured reservoir research.In order to realize the automatic extraction and accurate description of the linear features of digital outcrop cracks,this paper proposes a digital outcrop crack extraction method based on multi-scale Beamlet transform.The multi-scale adaptive enhancement algorithm was used to enhance the gray image to reduce the interference of background noise and uneven illumination,and the crack binary image was obtained by using Otus threshold method to split cracks and background.Beamlet transform was applied to the binary image to get the crack linear feature.The discrete crack line segments were connected.The experimental results show that compared with Canny edge detection algorithm and Hough transform algorithm,this method has better anti-noise ability,and the extracted crack linear features are more accurate and complete.By using adaptive enhancement algorithm and discrete line connection algorithm,the problems of uneven illumination and line disconnection are reduced,and the advantages of Beamlet algorithm in linear feature extraction are brought into full play.

关 键 词：BEAMLET变换 自适应增强 裂缝提取 数字地质露头 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置] TP3[自动化与计算机技术—控制科学与工程]