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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. DOI: 10.15898/j.cnki.11-2131/td.2016.06.005
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. DOI: 10.15898/j.cnki.11-2131/td.2016.06.005
Yu WANG, Chan JIN, Li-hua WANG, Jian-qiang WANG, Zheng JIANG, Yan-fei WANG. Pore Segmentation Methods Based on Gray Scale of Scanning Electron Microscopy Images[J]. Rock and Mineral Analysis, 2016, 35(6): 595-602. DOI: 10.15898/j.cnki.11-2131/td.2016.06.005
Citation: Yu WANG, Chan JIN, Li-hua WANG, Jian-qiang WANG, Zheng JIANG, Yan-fei WANG. Pore Segmentation Methods Based on Gray Scale of Scanning Electron Microscopy Images[J]. Rock and Mineral Analysis, 2016, 35(6): 595-602. DOI: 10.15898/j.cnki.11-2131/td.2016.06.005

基于SEM图像灰度水平的页岩孔隙分割方法研究

Pore Segmentation Methods Based on Gray Scale of Scanning Electron Microscopy Images

  • 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。

     

    Abstract: Microscopic pore structures of shale are the basis for investigating the adsorption and migration mechanism of shale gas and building a geological model. Ar ion milling combined with Scanning Electron Microscopy (SEM) is the main technique for analyzing microscopic pore structures of shale. However, previous research focused mainly on pore classification and lacked insufficient studies on the quantitative characteristics of pore structures. In order to conduct quantitative research on pore structures and improve the quality of pore segmentation, edge detection, watershed, auto and manual thresholding methods were used in this study to perform segmentation of mineral matrix pore and organic matter pore based on SEM images. By comparing results obtained from all of these methods, the conclusion drawn was that the manual thresholding method could reflect pores with diameters larger than 1 nm and identify the organic matter, pores and brittle minerals accurately by selecting a suitable segmentation thresholding value, guaranteeing the analysis to be closer to the true states. The proposed method provides a more effective method for quantitative analyses of shale pore structures.

     

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