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dc.contributor.authorWang, Yuzhu
dc.contributor.authorAlzaben, Abdulaziz
dc.contributor.authorArns, Christoph H.
dc.contributor.authorSun, Shuyu
dc.date.accessioned2021-03-22T06:18:32Z
dc.date.available2021-03-22T06:18:32Z
dc.date.issued2021-02-06
dc.date.submitted2020-04-09
dc.identifier.citationWang, Y., Alzaben, A., Arns, C. H., & Sun, S. (2021). Image-based rock typing using local homogeneity filter and Chan-Vese model. Computers & Geosciences, 150, 104712. doi:10.1016/j.cageo.2021.104712
dc.identifier.issn0098-3004
dc.identifier.doi10.1016/j.cageo.2021.104712
dc.identifier.urihttp://hdl.handle.net/10754/668177
dc.description.abstractImage-based rock typing is carried out to classify an image of the heterogeneous rock sample into different rock types where each rock type can be treated as a homogeneous porous medium. In this study, we propose an innovative method for rock typing of the heterogeneous rock sample via three steps. First, the target image, a segmented binary image with two phases of pore and solid, is consecutively inputted into two filters of a local homogeneity filter and an average filter to increase the contrast between different rock types and decrease the contrast within each single rock type. Second, Chan-Vese model is applied to classify the filtered image into different rock types. Third, a thresholding is used to remove the particles, which are treated as noisy particles, smaller than a given preset size. The main idea of the local homogeneity filtering introduced in this study is undertaken by counting the number of pixels that possess the same phases as the center pixel within a 3 × 3 pixels neighborhood. This process is carried out iteratively, which means the previously estimated pixel will be used in the estimation of its neighbor unprocessed pixels. We demonstrate the application of the proposed method in several heterogeneous images and present good performance.
dc.description.sponsorshipThe four authors cheerfully acknowledge that this work is supported by King Abdullah University of Science and Technology (KAUST) through the grants BAS/1/1351-01, URF/1/4074-01, and URF/1/3769-01. For computer time, this research used the resources of the Supercomputing Laboratory at King Abdullah University of Science & Technology (KAUST) in Thuwal, Saudi Arabia.
dc.publisherElsevier BV
dc.relation.urlhttps://linkinghub.elsevier.com/retrieve/pii/S0098300421000261
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in Computers and Geosciences. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Geosciences, [150, , (2021-02-06)] DOI: 10.1016/j.cageo.2021.104712 . © 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleImage-based rock typing using local homogeneity filter and Chan-Vese model
dc.typeArticle
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentComputational Transport Phenomena Lab
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentEarth Science and Engineering Program
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.identifier.journalComputers and Geosciences
dc.rights.embargodate2023-03-13
dc.eprint.versionPost-print
dc.contributor.institutionSchool of Minerals and Energy Resources Engineering (MERE), Faculty of Engineering, University of New South Wales (UNSW), Sydney, Australia
dc.identifier.volume150
dc.identifier.pages104712
kaust.personWang, Yuzhu
kaust.personAlzaben, Abdulaziz
kaust.personSun, Shuyu
kaust.grant.numberBAS/1/1351-01
kaust.grant.numberURF/1/3769-01
kaust.grant.numberURF/1/4074-01
dc.date.accepted2021-01-31
dc.relation.issupplementedbygithub:yuzhu561/Rock_Typing_CV
dc.identifier.eid2-s2.0-85102311052
display.relations<b>Is Supplemented By:</b><br/> <ul><li><i>[Software]</i> <br/> Title: yuzhu561/Rock_Typing_CV: This code is developed for image-based rock typing of porous media using Chan-Vese model. Publication Date: 2020-04-15. github: <a href="https://github.com/yuzhu561/Rock_Typing_CV" >yuzhu561/Rock_Typing_CV</a> Handle: <a href="http://hdl.handle.net/10754/668349" >10754/668349</a></a></li></ul>
kaust.acknowledged.supportUnitSupercomputing Laboratory


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