Estimation of Sandstone Permeability with SEM Images Based on Fractal Theory
Permeability is one of the key parameters for quantitatively evaluating groundwater resources and accurately predicting the rates of water inflows into coal mines. This paper presents an efficient method to estimate the macroscopic permeability by using the scanning electron microscopy (SEM) images....
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Veröffentlicht in: | Transport in porous media 2019-02, Vol.126 (3), p.701-712 |
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description | Permeability is one of the key parameters for quantitatively evaluating groundwater resources and accurately predicting the rates of water inflows into coal mines. This paper presents an efficient method to estimate the macroscopic permeability by using the scanning electron microscopy (SEM) images. A correlation between the microscopic features of sandstone porosity and the macropermeability is approached by an image identification technique. Firstly, the gray images were transformed into the binary images by using the histogram of the entropy method. Then, the Green and Euler distance methods were applied to calculate the length and area of the pores, and the fractal parameters were estimated according to the slit island method. Based on the theory of microscopic seepage flow, the seepage coefficient and permeability were calculated by fractal parameters. Typical water-bearing sandstone samples in the Kailuan coal field area in North China were selected to demonstrate the methodology. SEM microscopic images of nine groups of sandstone samples collected at different depths (from the outcrop to the deep mines) were analyzed. Based on the theoretical model of micropore structures and the fractal theory, the permeabilities were estimated. The results provide insights for understanding the hydraulic properties of the sandstone. |
doi_str_mv | 10.1007/s11242-018-1167-2 |
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This paper presents an efficient method to estimate the macroscopic permeability by using the scanning electron microscopy (SEM) images. A correlation between the microscopic features of sandstone porosity and the macropermeability is approached by an image identification technique. Firstly, the gray images were transformed into the binary images by using the histogram of the entropy method. Then, the Green and Euler distance methods were applied to calculate the length and area of the pores, and the fractal parameters were estimated according to the slit island method. Based on the theory of microscopic seepage flow, the seepage coefficient and permeability were calculated by fractal parameters. Typical water-bearing sandstone samples in the Kailuan coal field area in North China were selected to demonstrate the methodology. SEM microscopic images of nine groups of sandstone samples collected at different depths (from the outcrop to the deep mines) were analyzed. Based on the theoretical model of micropore structures and the fractal theory, the permeabilities were estimated. The results provide insights for understanding the hydraulic properties of the sandstone.</description><identifier>ISSN: 0169-3913</identifier><identifier>EISSN: 1573-1634</identifier><identifier>DOI: 10.1007/s11242-018-1167-2</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Civil Engineering ; Classical and Continuum Physics ; Coal mines ; Earth and Environmental Science ; Earth Sciences ; Fractal models ; Fractals ; Geotechnical Engineering & Applied Earth Sciences ; Groundwater ; Histograms ; Hydrogeology ; Hydrology/Water Resources ; Industrial Chemistry/Chemical Engineering ; Inflow ; Outcrops ; Parameter estimation ; Permeability ; Porosity ; Sandstone ; Scanning electron microscopy ; Seepage ; Theory</subject><ispartof>Transport in porous media, 2019-02, Vol.126 (3), p.701-712</ispartof><rights>Springer Nature B.V. 2018</rights><rights>Copyright Springer Nature B.V. 2019</rights><rights>Transport in Porous Media is a copyright of Springer, (2018). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c344t-27685e3d22a58aba8826d8d853fb5705486210ebaf3dea8fb6dda6654d44823b3</citedby><cites>FETCH-LOGICAL-c344t-27685e3d22a58aba8826d8d853fb5705486210ebaf3dea8fb6dda6654d44823b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11242-018-1167-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11242-018-1167-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Yu, Qingyang</creatorcontrib><creatorcontrib>Dai, Zhenxue</creatorcontrib><creatorcontrib>Zhang, Zhien</creatorcontrib><creatorcontrib>Soltanian, Mohamad Reza</creatorcontrib><creatorcontrib>Yin, Shangxian</creatorcontrib><title>Estimation of Sandstone Permeability with SEM Images Based on Fractal Theory</title><title>Transport in porous media</title><addtitle>Transp Porous Med</addtitle><description>Permeability is one of the key parameters for quantitatively evaluating groundwater resources and accurately predicting the rates of water inflows into coal mines. This paper presents an efficient method to estimate the macroscopic permeability by using the scanning electron microscopy (SEM) images. A correlation between the microscopic features of sandstone porosity and the macropermeability is approached by an image identification technique. Firstly, the gray images were transformed into the binary images by using the histogram of the entropy method. Then, the Green and Euler distance methods were applied to calculate the length and area of the pores, and the fractal parameters were estimated according to the slit island method. Based on the theory of microscopic seepage flow, the seepage coefficient and permeability were calculated by fractal parameters. Typical water-bearing sandstone samples in the Kailuan coal field area in North China were selected to demonstrate the methodology. SEM microscopic images of nine groups of sandstone samples collected at different depths (from the outcrop to the deep mines) were analyzed. Based on the theoretical model of micropore structures and the fractal theory, the permeabilities were estimated. The results provide insights for understanding the hydraulic properties of the sandstone.</description><subject>Civil Engineering</subject><subject>Classical and Continuum Physics</subject><subject>Coal mines</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Fractal models</subject><subject>Fractals</subject><subject>Geotechnical Engineering & Applied Earth Sciences</subject><subject>Groundwater</subject><subject>Histograms</subject><subject>Hydrogeology</subject><subject>Hydrology/Water Resources</subject><subject>Industrial Chemistry/Chemical Engineering</subject><subject>Inflow</subject><subject>Outcrops</subject><subject>Parameter estimation</subject><subject>Permeability</subject><subject>Porosity</subject><subject>Sandstone</subject><subject>Scanning electron microscopy</subject><subject>Seepage</subject><subject>Theory</subject><issn>0169-3913</issn><issn>1573-1634</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp9kM1KAzEURoMoWEcfwF3AdTQ3f5MutbRaqCi0rkOmybRT2pmapEjf3pQRXOnqbs53DxyEboHeA6XlQwRgghEKmgCokrAzNABZcgKKi3M0oKCGhA-BX6KrGDeU5pUWAzQbx9TsbGq6Fnc1ntvWxdS1Hr_7sPO2arZNOuKvJq3xfPyKpzu78hE_2egdzpNJsMtkt3ix9l04XqOL2m6jv_m5BfqYjBejFzJ7e56OHmdkyYVIhJVKS88dY1ZqW1mtmXLaacnrSpZUCq0YUF_ZmjtvdV0p56xSUjghNOMVL9Bd_3cfus-Dj8lsukNos9KwbJBSZsW_FJQlo0pqninoqWXoYgy-NvuQg4SjAWpOaU2f1uS05pQ2KwrE-k3MbLvy4ffz36NvSgh5oQ</recordid><startdate>20190201</startdate><enddate>20190201</enddate><creator>Yu, Qingyang</creator><creator>Dai, Zhenxue</creator><creator>Zhang, Zhien</creator><creator>Soltanian, Mohamad Reza</creator><creator>Yin, Shangxian</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>KB.</scope><scope>L6V</scope><scope>M7S</scope><scope>PDBOC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20190201</creationdate><title>Estimation of Sandstone Permeability with SEM Images Based on Fractal Theory</title><author>Yu, Qingyang ; Dai, Zhenxue ; Zhang, Zhien ; Soltanian, Mohamad Reza ; Yin, Shangxian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c344t-27685e3d22a58aba8826d8d853fb5705486210ebaf3dea8fb6dda6654d44823b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Civil Engineering</topic><topic>Classical and Continuum Physics</topic><topic>Coal mines</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Fractal models</topic><topic>Fractals</topic><topic>Geotechnical Engineering & Applied Earth Sciences</topic><topic>Groundwater</topic><topic>Histograms</topic><topic>Hydrogeology</topic><topic>Hydrology/Water Resources</topic><topic>Industrial Chemistry/Chemical Engineering</topic><topic>Inflow</topic><topic>Outcrops</topic><topic>Parameter estimation</topic><topic>Permeability</topic><topic>Porosity</topic><topic>Sandstone</topic><topic>Scanning electron microscopy</topic><topic>Seepage</topic><topic>Theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yu, Qingyang</creatorcontrib><creatorcontrib>Dai, Zhenxue</creatorcontrib><creatorcontrib>Zhang, Zhien</creatorcontrib><creatorcontrib>Soltanian, Mohamad Reza</creatorcontrib><creatorcontrib>Yin, Shangxian</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Materials Science Database</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Materials Science Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><jtitle>Transport in porous media</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yu, Qingyang</au><au>Dai, Zhenxue</au><au>Zhang, Zhien</au><au>Soltanian, Mohamad Reza</au><au>Yin, Shangxian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimation of Sandstone Permeability with SEM Images Based on Fractal Theory</atitle><jtitle>Transport in porous media</jtitle><stitle>Transp Porous Med</stitle><date>2019-02-01</date><risdate>2019</risdate><volume>126</volume><issue>3</issue><spage>701</spage><epage>712</epage><pages>701-712</pages><issn>0169-3913</issn><eissn>1573-1634</eissn><abstract>Permeability is one of the key parameters for quantitatively evaluating groundwater resources and accurately predicting the rates of water inflows into coal mines. This paper presents an efficient method to estimate the macroscopic permeability by using the scanning electron microscopy (SEM) images. A correlation between the microscopic features of sandstone porosity and the macropermeability is approached by an image identification technique. Firstly, the gray images were transformed into the binary images by using the histogram of the entropy method. Then, the Green and Euler distance methods were applied to calculate the length and area of the pores, and the fractal parameters were estimated according to the slit island method. Based on the theory of microscopic seepage flow, the seepage coefficient and permeability were calculated by fractal parameters. Typical water-bearing sandstone samples in the Kailuan coal field area in North China were selected to demonstrate the methodology. SEM microscopic images of nine groups of sandstone samples collected at different depths (from the outcrop to the deep mines) were analyzed. Based on the theoretical model of micropore structures and the fractal theory, the permeabilities were estimated. The results provide insights for understanding the hydraulic properties of the sandstone.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s11242-018-1167-2</doi><tpages>12</tpages></addata></record> |
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subjects | Civil Engineering Classical and Continuum Physics Coal mines Earth and Environmental Science Earth Sciences Fractal models Fractals Geotechnical Engineering & Applied Earth Sciences Groundwater Histograms Hydrogeology Hydrology/Water Resources Industrial Chemistry/Chemical Engineering Inflow Outcrops Parameter estimation Permeability Porosity Sandstone Scanning electron microscopy Seepage Theory |
title | Estimation of Sandstone Permeability with SEM Images Based on Fractal Theory |
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