ISSN 1004-4140
CN 11-3017/P

基于时间演化的天然气水合物CT图像阈值分割

陈亮, 叶旺全, 李承峰, 孙建业, 郑荣儿

陈亮, 叶旺全, 李承峰, 等. 基于时间演化的天然气水合物CT图像阈值分割[J]. CT理论与应用研究, 2023, 32(2): 171-178. DOI: 10.15953/j.ctta.2022.062.
引用本文: 陈亮, 叶旺全, 李承峰, 等. 基于时间演化的天然气水合物CT图像阈值分割[J]. CT理论与应用研究, 2023, 32(2): 171-178. DOI: 10.15953/j.ctta.2022.062.
CHEN L, YE W Q, LI C F, et al. Natural Gas Hydrate CT Image Threshold Segmentation Based on Time Evolution[J]. CT Theory and Applications, 2023, 32(2): 171-178. DOI: 10.15953/j.ctta.2022.062. (in Chinese).
Citation: CHEN L, YE W Q, LI C F, et al. Natural Gas Hydrate CT Image Threshold Segmentation Based on Time Evolution[J]. CT Theory and Applications, 2023, 32(2): 171-178. DOI: 10.15953/j.ctta.2022.062. (in Chinese).

基于时间演化的天然气水合物CT图像阈值分割

基金项目: 国家自然科学基金(CO2置换甲烷水合物前缘演化及其力学特性和置换效率响应(41976205))。
详细信息
    作者简介:

    陈亮: 男,中国海洋大学光电信息工程专业在读硕士研究生,主要从事图像处理及其应用相关研究,E-mail:cl6707@std.ouc.edu.cn

    李承峰: 男,青岛海洋地质研究所天然气水合物重点实验室工程师,主要从事天然气水合物微尺度实验探测技术研究,E-mail:lchengfeng@mail.cgs.gov.cn

    通讯作者:

    李承峰*

  • 中图分类号: P  631.3;O  242

Natural Gas Hydrate CT Image Threshold Segmentation Based on Time Evolution

  • 摘要: 微米X射线计算机断层扫描作为一种数字岩心探测手段,被广泛应用于研究含天然气水合物沉积物赋存形态,但由于水合物与水对X射线的衰减系数相近,二者在CT图像中灰度区间存在交集,导致在从CT图像上对水合物与水进行分割时存在强非唯一性。为提高对CT图像中水合物与水阈值分割的准确性,本文通过分析天然气水合物生长过程中不同时刻CT图像直方图特征,提出归一化CT图像及其直方图的方法。首先选定甲烷气与石英砂的峰值灰度基准;然后用高斯函数分别对当前CT图像直方图中的甲烷气与石英砂曲线进行拟合,得到当前CT图像直方图中的甲烷气与石英砂峰值灰度;再将当前CT图像直方图中的甲烷气峰值灰度与石英砂峰值灰度归一化到选定的峰值灰度基准;进而用归一化的直方图对CT图像进行归一化;最后根据归一化灰度直方图的变化趋势,定量统计得到CT图像中水合物增加和气-水减少的灰度区间,完成图像中不同组分的阈值划分。实验结果表明,提出的阈值分割方法能够为天然气水合物CT图像中水合物与水边界的确定和水合物饱和度计算提供定量的依据,具有实际的工程应用价值。
    Abstract: Micro-scale X-ray computed tomography (CT) has been widely used to study the occurrence forms of gas hydrate-bearing sediments. However, the similarity between the X-ray attenuation coefficient of hydrate and that of water leads to a strong non-uniqueness in their phase differentiation in CT images. To improve threshold segmentation accuracy between hydrate and water in CT images, this study proposes a CT image and histogram normalized method by analyzing the histogram characteristics of CT images at different times during the growth process of natural gas hydrate. First, the peak gray value baseline of methane gas and quartz sand was selected. Then, a Gaussian function was used to fit the curves corresponding to methane gas and quartz sand in the current CT image histogram to obtain the peak gray values. In addition, the peak gray values of methane gas and quartz sand in the current CT image histogram were normalized to the chosen peak gray baseline. Subsequently, the normalized histogram was used to normalize the corresponding CT images. Finally, according to the changing trend of normalized gray histogram curves, the increasing gray ranges of hydrate and decreasing gray ranges of gas-water in CT images were obtained quantitatively, which guided threshold segmentation of CT images. Experimental results show that the proposed threshold segmentation method can provide a basis for phase differentiation between hydrate and water in CT images, improving the threshold segmentation accuracy.
  • 图  1   CT灰度图像直方图归一化流程图

    Figure  1.   Histogram normalization flow chart of CT gray image

    图  2   灰度直方图归一化对比(切片编号150)

    Figure  2.   Comparison of histogram curves before and after normalization(slice 150)

    图  3   水合物与水混合峰区域

    Figure  3.   Mixing peak region of hydrate and water

    图  4   图像归一化对比(切片编号150)及三维数字岩心图像

    Figure  4.   Image normalization contrast (slice 150) and 3D digital core

    图  5   不同时刻CT图像直方图曲线差值(切片编号150)

    Figure  5.   Histogram curves of CT images subtracted at different times(slice 150)

    图  6   基于本文阈值分割方法得到的伪彩色三维数字岩心及图像的孔隙局部放大图像

    Figure  6.   Pseudo-color digital core and local pore magnification image obtained based on threshold segmentation method used in this study

    图  7   饱和度参数对比图

    Figure  7.   Comparison of hydrate saturation

    表  1   CT图像中各种组分的灰度区间

    Table  1   Gray intervals of various components of CT images

    反应时间/h灰度区间(0~255)
    甲烷气甲烷水合物
    00~5859~156157~255
    300~5859~9697~156157~255
    340~5858~9697~156157~255
    480~5859~9697~156157~255
    720~61 62~105106~156 157~255
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-04-11
  • 修回日期:  2022-08-31
  • 录用日期:  2022-09-05
  • 网络出版日期:  2022-10-16
  • 发布日期:  2023-03-30

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