Hamed Lamei Ramandi, Ryan T. Armstrong, Peyman Mostaghimi
{"title":"微ct图像校正改进裂缝孔径测量","authors":"Hamed Lamei Ramandi, Ryan T. Armstrong, Peyman Mostaghimi","doi":"10.1016/j.csndt.2016.03.001","DOIUrl":null,"url":null,"abstract":"<div><p>A novel technique for the accurate measurement and adjustment of fracture apertures in digital images of fractured media is presented. We utilize X-ray micro-computed tomography to image a highly fractured coal sample and collect high-resolution scanning electron microscope (SEM) images from the samples surface to facilitate segmentation of coal fractures. The gray-scale micro-CT values at the mid-point of fractures are obtained and correlated to aperture sizes measured with the higher resolution SEM data. Afterwards, the micro-CT images are upsampled to enable assignment of aperture sizes smaller than the image resolution. We initially segment the coal image, upsample the segmented image, and then re-calibrate the fracture aperture sizes. The final calibrated segmented image contains the fracture network acquired from the micro-CT data with precise aperture sizes assigned based on the high-resolution SEM data. To illustrate the importance of accurate aperture measurement, two coal subsets are tested. The permeabilities before and after applying the calibration method are measured. The results show a significant change in numerical permeabilities after applying the calibration method. This indicates that a large amount of information is potentially omitted when utilizing standard image segmentation tools to segment fractured media.</p></div>","PeriodicalId":100221,"journal":{"name":"Case Studies in Nondestructive Testing and Evaluation","volume":"6 ","pages":"Pages 4-13"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.csndt.2016.03.001","citationCount":"49","resultStr":"{\"title\":\"Micro-CT image calibration to improve fracture aperture measurement\",\"authors\":\"Hamed Lamei Ramandi, Ryan T. Armstrong, Peyman Mostaghimi\",\"doi\":\"10.1016/j.csndt.2016.03.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>A novel technique for the accurate measurement and adjustment of fracture apertures in digital images of fractured media is presented. We utilize X-ray micro-computed tomography to image a highly fractured coal sample and collect high-resolution scanning electron microscope (SEM) images from the samples surface to facilitate segmentation of coal fractures. The gray-scale micro-CT values at the mid-point of fractures are obtained and correlated to aperture sizes measured with the higher resolution SEM data. Afterwards, the micro-CT images are upsampled to enable assignment of aperture sizes smaller than the image resolution. We initially segment the coal image, upsample the segmented image, and then re-calibrate the fracture aperture sizes. The final calibrated segmented image contains the fracture network acquired from the micro-CT data with precise aperture sizes assigned based on the high-resolution SEM data. To illustrate the importance of accurate aperture measurement, two coal subsets are tested. The permeabilities before and after applying the calibration method are measured. The results show a significant change in numerical permeabilities after applying the calibration method. This indicates that a large amount of information is potentially omitted when utilizing standard image segmentation tools to segment fractured media.</p></div>\",\"PeriodicalId\":100221,\"journal\":{\"name\":\"Case Studies in Nondestructive Testing and Evaluation\",\"volume\":\"6 \",\"pages\":\"Pages 4-13\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.csndt.2016.03.001\",\"citationCount\":\"49\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Case Studies in Nondestructive Testing and Evaluation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2214657116300028\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Case Studies in Nondestructive Testing and Evaluation","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214657116300028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Micro-CT image calibration to improve fracture aperture measurement
A novel technique for the accurate measurement and adjustment of fracture apertures in digital images of fractured media is presented. We utilize X-ray micro-computed tomography to image a highly fractured coal sample and collect high-resolution scanning electron microscope (SEM) images from the samples surface to facilitate segmentation of coal fractures. The gray-scale micro-CT values at the mid-point of fractures are obtained and correlated to aperture sizes measured with the higher resolution SEM data. Afterwards, the micro-CT images are upsampled to enable assignment of aperture sizes smaller than the image resolution. We initially segment the coal image, upsample the segmented image, and then re-calibrate the fracture aperture sizes. The final calibrated segmented image contains the fracture network acquired from the micro-CT data with precise aperture sizes assigned based on the high-resolution SEM data. To illustrate the importance of accurate aperture measurement, two coal subsets are tested. The permeabilities before and after applying the calibration method are measured. The results show a significant change in numerical permeabilities after applying the calibration method. This indicates that a large amount of information is potentially omitted when utilizing standard image segmentation tools to segment fractured media.