| 基于SEM图像灰度水平的页岩孔隙分割方法研究 |
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| 引用本文： | 王羽,金婵,汪丽华,王建强,姜政,王彦飞.基于SEM图像灰度水平的页岩孔隙分割方法研究[J].岩矿测试,2016,35(6):595-602. |
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| 作者姓名： | 王羽 金婵 汪丽华 王建强 姜政 王彦飞 |
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| 作者单位： | 中国科学院微观界面物理与探测重点实验室, 上海 201800;中国科学院上海应用物理研究所上海光源, 上海 201204,中国科学院微观界面物理与探测重点实验室, 上海 201800;中国科学院上海应用物理研究所上海光源, 上海 201204,中国科学院微观界面物理与探测重点实验室, 上海 201800;中国科学院上海应用物理研究所上海光源, 上海 201204,中国科学院微观界面物理与探测重点实验室, 上海 201800;中国科学院上海应用物理研究所上海光源, 上海 201204,中国科学院微观界面物理与探测重点实验室, 上海 201800;中国科学院上海应用物理研究所上海光源, 上海 201204,中国科学院地质与地球物理研究所, 北京 100029 |
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| 基金项目： | 中国科学院战略性先导科技专项（B类）“页岩三维成像实验技术和数据获取技术”（XDB10020102）；国家杰出青年科学基金项目（41325016） |
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| 摘 要： | 微观孔隙结构是研究页岩气吸附运移机制和建立地质模型的基础,氩离子抛光-扫描电子显微镜(SEM)技术是开展此项研究的主要实验方法,但已有的研究大多是关注页岩孔隙分类,较少从定量角度表征其特征。为开展页岩微观孔隙结构定量研究,提高孔隙分割质量,本研究分别利用边缘检测分割法、流域分割法、手动和自动阈值分割法对页岩无机孔和有机孔二次电子图像进行分割实验,对比不同方法的分割效果。结果表明,通过选取合适的分割阈值,基于SEM图像的手动阈值分割法能够表征1 nm以上的孔隙,准确地识别有机质与脆性矿物边缘、孔隙与有机质边缘,使得页岩孔隙提取结果趋近于真实,能更有效地对页岩孔隙结构进行定量分析。
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| 关 键 词： | 富有机质页岩 SEM图像 孔隙分割 阈值法 |
| 收稿时间： | 2016/5/23 0:00:00 |
| 修稿时间： | 8/9/2016 12:00:00 AM |
Pore Segmentation Methods Based on Gray Scale of Scanning Electron Microscopy Images |
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| WANG Yu,JIN Chan,WANG Li-hu,WANG Jian-qiang,JIANG Zheng and WANG Yan-fei.Pore Segmentation Methods Based on Gray Scale of Scanning Electron Microscopy Images[J].Rock and Mineral Analysis,2016,35(6):595-602. |
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| Authors: | WANG Yu JIN Chan WANG Li-hu WANG Jian-qiang JIANG Zheng and WANG Yan-fei |
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| Institution: | Key Laboratory of Interfacial Physics and Technology, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China;Shanghai Synchrotron Radiation Facility, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201204, China,Key Laboratory of Interfacial Physics and Technology, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China;Shanghai Synchrotron Radiation Facility, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201204, China,Key Laboratory of Interfacial Physics and Technology, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China;Shanghai Synchrotron Radiation Facility, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201204, China,Key Laboratory of Interfacial Physics and Technology, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China;Shanghai Synchrotron Radiation Facility, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201204, China,Key Laboratory of Interfacial Physics and Technology, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China;Shanghai Synchrotron Radiation Facility, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201204, China and Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China |
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| Abstract: | Microscopic pore structures of shale are the basis of investigating the adsorption and migration mechanism of shale gas and building geological model. Ar ion milling combined with scanning electron microscopy is the main technique to carry out such researches. However, previous researches mainly focused on the pore classification,and pore structures still lacked quantification and needed further study. In this study, edge detection, watershed,auto and manual thresholding methods were adopted to perform pore segmentation of mineral matrix pore and organic matter pore based on secondary scanning electron images. By comparisons, the results indicated that manual thresholding method was more suitable for shale pore (>1 nm) segmentation. Thresholding could identify the organic matter, pores and brittle minerals accurately by selecting accurate segmentation thresholding value, guaranteeing the results converged to the true states and providing an effective method for shale pore structures quantification. |
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| Keywords: | organic rich shale SEM image pore segmentation threshold method |
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