页岩微观结构灰度图像的标准化方法  

A method of gray-level image standardization for shale microscopic structure characterization

作　　者：俞雨溪 王宗秀[1,2,3] 程明 尹锦涛[5] YU Yuxi;WANG Zongxiu;CHENG Ming;YIN Jintao(Institute of Geomechanics,Chinese Academy of Geological Sciences,Beijing 100081,China;Key Laboratory of Paleomagnetism and Tectonic Reconstruction of Ministry of Natural Resources,Beijing 100081,China;Key Lab of Shale Oil and Gas Geological Survey,Chinese Academy of Geological Sciences,Beijing 100081,China;Key Laboratory of Petroleum Resources Research,Institute of Geology and Geophysics,Chinese Academy of Sciences,Beijing 100029,China;Research Institute of Exploration and Development,Shaanxi Yanchang Petroleum (Group) Co.,Ltd.,Xi’an 710075,China)

机构地区：[1]中国地质科学院地质力学研究所,北京100081 [2]国土资源部古地磁与古构造重建重点实验室,北京100081 [3]中国地质科学院页岩油气调查评价重点实验室,北京100081 [4]中国科学院地质与地球物理研究所,北京100029 [5]陕西延长石油(集团)有限责任公司研究院,陕西西安710075

出　　处：《煤炭学报》2019年第7期2178-2187,共10页Journal of China Coal Society

基　　金：国家自然科学基金资助项目(41802178);中国地质科学院基本科研业务费资助项目(JYYWF20181201);中国地质调查局地质调查基金资助项目(DD20160183)

摘　　要：采用灰度图像分析方法获取页岩孔隙结构参数是目前页岩微观结构表征的一种重要手段。在扫描成像过程中,往往需要根据样品自身特点调节亮度、对比度等参数以达到较好的成像效果,这会导致不同视域、不同样品的图像灰度分布特征发生变化,从而导致识别孔隙的灰度阈值产生差异。为了实现统一标准识别页岩孔隙,研究以SEM图像为例,由图像灰度分布影响因素分析入手,在提取一系列标志参考物灰度的基础上,通过合成灰度累计概率分布建立了待校正图像的代表性灰度分布,在此基础上确定了待标准图像与标准图像合成灰度累计概率分布之间的映射关系,采用图像灰度直方图匹配算法实现了图像标准化。研究结果表明,页岩中的孔隙、有机质、自生石英、黄铁矿等4种组分组合后可覆盖整个图像灰度分布,是有效的标志参考物组合。利用该标志物组合所合成灰度累计概率分布作为不同图像间的对比参数进行标准化,可以消除组分含量差异对灰度分布的影响,达到校正对比度和亮度等扫描参数设置差异对图像灰度的影响。经验证,该方法对采用不同拍摄参数的图像均具有较好的应用效果,经过标准化处理后的图像能够实现同一灰度阈值自动识别页岩孔隙和有机质等地质元素,提高了图像提取孔隙结构参数的可对比性,为页岩微观图像孔隙结构定量分析提供了可靠基础。Gray-level image analysis is important in shale pore structure characterization.To obtain good imaging result,it is necessary to adjust the brightness and contrast for the different fields of view or different samples when capturing the image.This will bring difference in gray-level distribution,which directly results in the variation of threshold value for pores.To solve this problem,the SEM image was taken as an example to analyze the factors that can influence the grey level of image.The grey level distribution of the uncorrected image is represented by the integrated cumulative probability distribution of the references,which are based on the density probability distribution extracted from the pyrites,authigenic quartz,organic matter and pore in shale.By establishing relations with the standardized image,the correction can be realized based on the theory of gray level histogram specification.The results show that the grey-level distributions of the marker assemblage can cover the whole grey-level range of the image.Due to the adoption of the marker assemblage,the influence of the shale compositions on the grey level of the image can be eliminated and the discrepancies in the grey level of image induced by different scanning parameters of brightness and contrast can be corrected.The effect of image standardization was verified and it can be applied to images scanned under different situations.The results show that the proposed standardization method can improve the automatic identification of pore and organic matter by using the same threshold value,which will lay a solid foundation for microscopic image analysis and provide comparable and reliable data for the quantitative characterization of shale pore structure.

关 键 词：页岩 孔隙结构 灰度 标准化 图像分析 

分 类 号：P618.13[天文地球—矿床学]