2025年7月23日 星期三
岩石力学与工程学报  2024, Vol. 43 Issue (S1): 3175-3186    DOI: 10.13722/j.cnki.jrme.2023.0887
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基于像素空间信息的孔内低照度图像孔隙结构量化方法研究
汪进超1,韩增强1,王益腾1,王  超1,张国华2
(1. 中国科学院武汉岩土力学研究所 岩土力学与工程国家重点实验室,湖北 武汉  430071;2. 中国地质大学(武汉) 工程学院,湖北 武汉  430074)
Quantification method of pore structure in low illuminance borehole images based on pixel spatial information
WANG Jinchao1,HAN Zengqiang1,WANG Yiteng1,WANG Chao1,ZHANG Guohua2
(1. State Key Laboratory of Geomechanics and Geotechnical Engineering,Institute of Rock and Soil Mechanics,Chinese Academy of Sciences,Wuhan,Hubei 430071,China;2. Faculty of Engineering,China University of Geosciences(Wuhan),
Wuhan,Hubei 430074,China)
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摘要 鉴于目前井下复杂环境状态下,低反射特性岩壁上孔隙结构原位探测过程中往往存在的图像清晰度不够以及定量表征不准确等技术难题,提出一种基于像素空间信息的孔内低照度图像孔隙结构量化方法,通过同步利用孔壁图像和点云数据,得到非标准圆柱钻孔形态的孔壁像素空间特征信息,实现复杂地质条件下低反射特性岩层的孔隙结构定量化过程。首先,基于实际钻孔环境及测试过程中容易形成的具有纹理明暗交替现象的低照度孔壁图像特征,构建符合实际测孔状态的孔壁偏心图像校正模型,形成能够有效削弱孔壁纹理明暗现象的余弦明暗纹理抑制函数;随后,提出一种基于细节特征加权融合的低照度孔壁图像增强算法,增强低照度孔壁图像的纹理信息;最后,融合像素空间单元格的划分和像素空间点水平与垂直尺度的计算,形成利用像素空间信息的孔隙结构量化方法。同时,结合实际案例分析,验证该方法的正确性与优越性。结果表明,该方法能够得到非标准圆柱钻孔形态的孔壁像素空间特征信息,可以为复杂地质条件下低反射特性岩层的孔隙结构原位探测提供一种新的技术方法与手段。
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汪进超1
韩增强1
王益腾1
王 超1
张国华2
关键词 岩石力学孔隙结构图像处理定量表征像素空间低照度图像    
Abstract:Given the technical challenges of insufficient image clarity and inaccurate quantitative characterization in the in-situ detection of pore structures on low reflection rock walls,this paper proposes a quantification method of pore structure in low illuminance borehole images based on pixel spatial Information. By synchronously utilizing borehole wall images and point cloud data to obtain pixel spatial feature information of non-standard cylindrical borehole shapes,the quantification process of pore structure in low reflection characteristic rock layers under complex geological conditions is achieved. Firstly,based on the low illumination borehole wall image features with alternating light and dark textures that are often formed in the actual drilling environment and testing process,a borehole wall eccentricity image correction model that is suitable for the actual hole testing environment is constructed to form a cosine light and dark texture suppression function that can effectively weaken the hole wall light and dark texture phenomenon. Subsequently,a low illumination borehole wall image enhancement algorithm based on detail feature weighted fusion is proposed to enhance the texture information of low illumination borehole wall images. Finally,combining the division of pixel spatial cells and the calculation of horizontal and vertical scales of pixel spatial points,a pore structure quantification method utilizing pixel spatial information is formed. At the same time,combined with practical case analysis,the correctness and superiority of the method proposed in this paper are verified. The results show that the method can obtain pixel spatial feature information of borehole walls in non-standard cylindrical drilling shapes,which can provide a new technical method and means for in-situ detection of pore structures in low reflection characteristic rock layers under complex geological conditions.
Key wordsrock mechanics    pore structure    image processing    quantitative characterization    pixel space    low illumination images
    
引用本文:   
汪进超1,韩增强1,王益腾1,王 超1,张国华2. 基于像素空间信息的孔内低照度图像孔隙结构量化方法研究[J]. 岩石力学与工程学报, 2024, 43(S1): 3175-3186.
WANG Jinchao1,HAN Zengqiang1,WANG Yiteng1,WANG Chao1,ZHANG Guohua2. Quantification method of pore structure in low illuminance borehole images based on pixel spatial information. , 2024, 43(S1): 3175-3186.
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