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

被引:0
作者
Yu Y. [1 ,2 ,3 ]
Wang Z. [1 ,2 ,3 ]
Cheng M. [4 ]
Yin J. [5 ]
机构
[1] Institute of Geomechanics, Chinese Academy of Geological Sciences, Beijing
[2] Key Laboratory of Paleomagnetism and Tectonic Reconstruction of Ministry of Natural Resources, Beijing
[3] Key Lab of Shale Oil and Gas Geological Survey, Chinese Academy of Geological Sciences, Beijing
[4] Key Laboratory of Petroleum Resources Research, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing
[5] Research Institute of Exploration and Development, Shaanxi Yanchang Petroleum (Group) Co., Ltd., Xi'an
来源
Meitan Xuebao/Journal of the China Coal Society | 2019年 / 44卷 / 07期
关键词
Grey level; Image analysis; Pore structure; Shale; Standardization;
D O I
10.13225/j.cnki.jccs.2018.0792
中图分类号
学科分类号
摘要
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. © 2019, Editorial Office of Journal of China Coal Society. All right reserved.
引用
收藏
页码:2178 / 2187
页数:9
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