摘要
XCT(X-ray computed tomography)是一种高效评价页岩三维特征和非均质性的方法。阈值通常用于在背景图像上分割孔隙-裂缝,但是很少对多元素分割体CT(computed tomography)图像进行研究。为了获取不同元素在三维尺度上的分布特征,综合利用大津阈值分割算法和场发射环境扫描电镜提出了一种新的分割方法:首先确定不同元素分布的灰度值,根据灰度值把页岩分成几个不同的矿物组分区域,利用大津阈值算法求取每个矿物组分区域,利用分割方法处理的页岩样品叠加形成CT图像,另一个CT图像用于验证该方法。结果表明,多元素分割方法可以利用C_T计算的数值成功分割叠加的CT图像,该方法与实验室进行的XRD(X-ray diffraction)、总有机碳质量分数、孔隙度测试等结果相符;相同物源和矿物组分的样品在背散射电子(BSE)和CT图像上有相同的灰度区域分布;该方法根据灰度区域分布原理对相同物源、矿物组分的页岩样品进行分割,比人为CT图像叠加分割样品方法更有效、更准确。因此,在页岩XCT图像分割中,进一步采用扫描电镜和多重-大津阈值算法进行多分量分割,能更好地提高页岩XCT图像分割的精度,同时该算法也能对其他区块页岩XCT图像研究起到一定的指导作用。
X-ray computed tomography is an efficient method for evaluating 3D characteristics and heterogeneity of shales.A threshold is commonly used to separate pore-fractures from the background image,but few studies discussed the multi-component segmentation of computed tomography images.To obtain the distribution characteristics of different components in three dimensions,a new segmentation method is proposed based on the combination of a multi-Otsu threshold algorithm with scanning electron microscopy.The gray value distributions of different components are first determined by using the method,then,the shale components are divided into several groups based on these gray values.The threshold of each component group is determined by using the multi-Otsu threshold algorithm.The CT image stacks of two shale samples are processed by using the segmentation method,and another CT image stack is used to verify the method.The results show that the multi-component segmentation method can successfully segment CT image stacks by using the calculated values determined by CT,which agrees well with the measured values obtained from Xray diffraction,total organic carbon,and porosity tests in the laboratory;samples with similar provenances and mineral compositions have the same gray value distribution in the back scattering scanning electron microscopy and CT images;in the method,the shale sample of the same provenance and the mineral component is divided according to the distribution principle of the gray area,and it is more effective and more accurate than the method for overlaying the sample by the man-made CT image.Therefore,in shale XCT image segmentation,scanning electron microscopy and multi-Otsuthreshold algorithm are used for multi-component segmentation,which can better improve the accuracy of shale XCT image segmentation.At the same time,this algorithm can provide guidance for studying shale XCT images of other blocks.
引文
[1]张磊,姚军,孙海,等.基于数字岩心技术的气体解析/扩散格子Boltzmann模拟[J].石油学报,2015,36(3):361~365.
[2]刘学锋,张伟伟,孙建孟.三维数字岩心建模方法综述[J].地球物理学进展,2013,28(6):3066~3072.
[3]屈乐,孙卫,杜环虹,等.基于CT扫描的三维数字岩心孔隙结构表征方法及应用——以莫北油田116井区三工河组为例[J].现代地质,2014,28(1):190~196.
[4]刘伟,张德峰,刘海河,等.数字岩心技术在致密砂岩储层含油饱和度评价中的应用[J].断块油气田,2013,20(5):593~596.
[5]王晨晨,姚军,杨永飞,等.基于格子玻尔兹曼方法的碳酸盐岩数字岩心渗流特征分析[J].中国石油大学学报(自然科学版),2012,36(6):94~98.
[6]孙建孟,闫国亮,姜黎明,等.基于数字岩心研究流体性质对裂缝性低渗透储层弹性参数的影响规律[J].中国石油大学学报(自然科学版),2014,38(3):39~44.
[7]聂昕,邹长春,孟小红,等.页岩气储层岩石三维数字岩心建模——以导电性模型为例[J].天然气地球科学,2016,27(4):706~715.
[8]莫修文,张强,陆敬安.模拟退火法建立数字岩心的一种补充优化方案[J].地球物理学报,2016,59(5):1831~1838.
[9]王晨晨,姚军,杨永飞,等.碳酸盐岩双孔隙数字岩心结构特征分析[J].中国石油大学学报(自然科学版),2013,37(2):71~74.
[10]刘培刚,刘钰洋,潘懋,等.基于砂岩三维数字岩心图像的图像处理与相划分研究[J].科学技术与工程,2017,17(6):22~30.
[11]刘钰洋,潘懋.砂岩数字岩心的地层参数模拟与粗化方法研究[J].科学技术与工程,2017,17(15):48~56.
[12]李兴文,姜黎明,寇晓攀,等.利用格子Boltzmann方法确定岩石孔隙空间中的气水分布[J].西安石油大学学报(自然科学版),2017,32(3):49~54.
[13]刘向君,熊健,梁利喜,等.基于微CT技术的致密砂岩孔隙结构特征及其对流体流动的影响[J].地球物理学进展,2017,32(3):1019~1028.
[14]吴国铭,李熙喆,高树生,等.基于分形理论探究碳酸盐岩CT图像二值化最佳阈值[J].石油地球物理勘探,2017,52(5):1025~1032.
[15]李昂,于浩波,谢斌,等.基于有限体积法的致密油储层数字岩心中流动与传热研究[J].测井技术,2017,41(2):135~140.
[16]鄢友军,李隆新,徐伟,等.三维数字岩心流动模拟技术在四川盆地缝洞型储层渗流研究中的应用[J].天然气地球科学,2017,28(9):1425~1432.
[17]曹廷宽,刘成川,曾焱,等.基于CT扫描的低渗砂岩分形特征及孔渗参数预测[J].断块油气田,2017,24(5):657~661.
[18]崔利凯,孙建孟,闫伟超,等.基于多分辨率图像融合的多尺度多组分数字岩心构建[J].吉林大学学报(地球科学版),2017,47(6):1904~1912.
[19]邹友龙,谢然红,郭江峰,等.致密储层数字岩心重构及核磁共振响应模拟[J].中国石油大学学报(自然科学版),2015,39(6):63~71.
[20]刘学锋,刁庆雷,孙宝佃,等.采用多点地质统计法重建三维数字岩心[J].测井技术,2015,39(6):698~703.
[21]李易霖,张云峰,丛琳,等.X-CT扫描成像技术在致密砂岩微观孔隙结构表征中的应用——以大安油田扶余油层为例[J].吉林大学学报(地球科学版),2016,46(2):379~387.
[22]张思勤,汪志明,洪凯,等.基于格子Boltzmann方法的3D数字岩心渗流特征分析[J].测井技术,2016,40(1):18~22.
[23]聂昕,邹长春,孟小红,等.页岩气储层岩石三维数字岩心建模——以导电性模型为例[J].天然气地球科学,2016,27(4):706~715.
[24]王代刚,胡永乐.基于微焦点CT的三维数字岩心分析研究进展[J].大庆石油地质与开发,2015,34(6):62~70.
[25]Sezgin M.Survey over image thresholding techniques and quantitative performance evaluation[J].Journal of Electronic Imaging,2004,13:146~168.
[26]Cao L.The study of image segmentation algorithm based on OTSU method[M].Wuhan:Wuhan University of Technology,2008:11~15.
[27]印兴耀,秦秋萍,宗兆云.数字岩石物理中弹性参数的有限差分计算方法[J].地球物理学报,2016,59(10):3883~3890.
[28]孔强夫,周灿灿,李潮流,等.一种基于数字岩心表面弛豫率确定的新方法[J].科学技术与工程,2014,14(35):210~215.
[29]Ketcham R A,Carlson W D.Acquisition,optimization and interpretation of X-ray computed tomographic imagery:Applications to the geosciences[J].British Medical Journal,2001,27(4):381~400.