Automatic calculating grain size of gravels based on micro-resistivity image of well
Since the micro-resistivity imaging logging tool cannot achieve 360° full coverage imaging around the well, there will be interval blank zone, resulting in the missing information of geology. In order to measure the size of gravels from the images, this paper adopts the ordinary kriging interpolatio...
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| Veröffentlicht in: | Arabian journal of geosciences 2021-09, Vol.14 (17), Article 1794 |
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| creator | Li, Donghui Yuan, Rui Ding, Zhenfeng Xu, Rui |
| description | Since the micro-resistivity imaging logging tool cannot achieve 360° full coverage imaging around the well, there will be interval blank zone, resulting in the missing information of geology. In order to measure the size of gravels from the images, this paper adopts the ordinary kriging interpolation method to interpolate the missing images to restore the blank zone and then uses the automatic characterization method to measure the size of gravels on the restored images. The results show that the method can not only restore the outline and characteristics of the gravels in the blank zone and fill in the missing parts of the image effectively, but also measure the gravel grain size from the restored logging image directly, which greatly reduces the manual measurement workload. As well, there is slight difference between the measured size and the actual size of the gravels. This method can be applied to the automatic quantification of gravel grain size in uncored well sections, which will provide fine information for basic geological research in whole well. |
| doi_str_mv | 10.1007/s12517-021-07866-x |
| format | Article |
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In order to measure the size of gravels from the images, this paper adopts the ordinary kriging interpolation method to interpolate the missing images to restore the blank zone and then uses the automatic characterization method to measure the size of gravels on the restored images. The results show that the method can not only restore the outline and characteristics of the gravels in the blank zone and fill in the missing parts of the image effectively, but also measure the gravel grain size from the restored logging image directly, which greatly reduces the manual measurement workload. As well, there is slight difference between the measured size and the actual size of the gravels. This method can be applied to the automatic quantification of gravel grain size in uncored well sections, which will provide fine information for basic geological research in whole well.</description><identifier>ISSN: 1866-7511</identifier><identifier>EISSN: 1866-7538</identifier><identifier>DOI: 10.1007/s12517-021-07866-x</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Earth and Environmental Science ; Earth science ; Earth Sciences ; Electrical resistivity ; Geology ; Grain size ; Gravel ; Image restoration ; Imaging techniques ; Kriging interpolation ; Logging ; Original Paper ; Particle size ; Statistical methods</subject><ispartof>Arabian journal of geosciences, 2021-09, Vol.14 (17), Article 1794</ispartof><rights>Saudi Society for Geosciences 2021</rights><rights>Saudi Society for Geosciences 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2009-10fbc71cdb6467cedca7fd72f576de7ecf37ba7c0ef122283922032e1653a9d13</citedby><cites>FETCH-LOGICAL-c2009-10fbc71cdb6467cedca7fd72f576de7ecf37ba7c0ef122283922032e1653a9d13</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/s12517-021-07866-x$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12517-021-07866-x$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Li, Donghui</creatorcontrib><creatorcontrib>Yuan, Rui</creatorcontrib><creatorcontrib>Ding, Zhenfeng</creatorcontrib><creatorcontrib>Xu, Rui</creatorcontrib><title>Automatic calculating grain size of gravels based on micro-resistivity image of well</title><title>Arabian journal of geosciences</title><addtitle>Arab J Geosci</addtitle><description>Since the micro-resistivity imaging logging tool cannot achieve 360° full coverage imaging around the well, there will be interval blank zone, resulting in the missing information of geology. In order to measure the size of gravels from the images, this paper adopts the ordinary kriging interpolation method to interpolate the missing images to restore the blank zone and then uses the automatic characterization method to measure the size of gravels on the restored images. The results show that the method can not only restore the outline and characteristics of the gravels in the blank zone and fill in the missing parts of the image effectively, but also measure the gravel grain size from the restored logging image directly, which greatly reduces the manual measurement workload. As well, there is slight difference between the measured size and the actual size of the gravels. This method can be applied to the automatic quantification of gravel grain size in uncored well sections, which will provide fine information for basic geological research in whole well.</description><subject>Earth and Environmental Science</subject><subject>Earth science</subject><subject>Earth Sciences</subject><subject>Electrical resistivity</subject><subject>Geology</subject><subject>Grain size</subject><subject>Gravel</subject><subject>Image restoration</subject><subject>Imaging techniques</subject><subject>Kriging interpolation</subject><subject>Logging</subject><subject>Original Paper</subject><subject>Particle size</subject><subject>Statistical methods</subject><issn>1866-7511</issn><issn>1866-7538</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kEtPwzAQhC0EEqXwBzhZ4hzw2o2dHKuKl1SJSzlbjmNHrvIodlJafj1Og-DGaWelb3ZHg9AtkHsgRDwEoCmIhFBIiMg4Tw5naAajECnLzn81wCW6CmFLCM8iOEOb5dB3jeqdxlrVeqijbCtceeVaHNyXwZ0dt72pAy5UMCXuWtw47bvEm-BC7_auP2LXqOrEfpq6vkYXVtXB3PzMOXp_etysXpL12_PrarlONCUkT4DYQgvQZcEXXGhTaiVsKahNBS-NMNoyUSihibFAKc1YTilh1ABPmcpLYHN0N93d-e5jMKGX227wbXwpacohZ3m2GCk6UTFzCN5YufMxrj9KIHJsT07tydiePLUnD9HEJlOIcFsZ_3f6H9c3Sgtz0Q</recordid><startdate>20210901</startdate><enddate>20210901</enddate><creator>Li, Donghui</creator><creator>Yuan, Rui</creator><creator>Ding, Zhenfeng</creator><creator>Xu, Rui</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>L.G</scope></search><sort><creationdate>20210901</creationdate><title>Automatic calculating grain size of gravels based on micro-resistivity image of well</title><author>Li, Donghui ; Yuan, Rui ; Ding, Zhenfeng ; Xu, Rui</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2009-10fbc71cdb6467cedca7fd72f576de7ecf37ba7c0ef122283922032e1653a9d13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Earth and Environmental Science</topic><topic>Earth science</topic><topic>Earth Sciences</topic><topic>Electrical resistivity</topic><topic>Geology</topic><topic>Grain size</topic><topic>Gravel</topic><topic>Image restoration</topic><topic>Imaging techniques</topic><topic>Kriging interpolation</topic><topic>Logging</topic><topic>Original Paper</topic><topic>Particle size</topic><topic>Statistical methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Donghui</creatorcontrib><creatorcontrib>Yuan, Rui</creatorcontrib><creatorcontrib>Ding, Zhenfeng</creatorcontrib><creatorcontrib>Xu, Rui</creatorcontrib><collection>CrossRef</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Arabian journal of geosciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Donghui</au><au>Yuan, Rui</au><au>Ding, Zhenfeng</au><au>Xu, Rui</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Automatic calculating grain size of gravels based on micro-resistivity image of well</atitle><jtitle>Arabian journal of geosciences</jtitle><stitle>Arab J Geosci</stitle><date>2021-09-01</date><risdate>2021</risdate><volume>14</volume><issue>17</issue><artnum>1794</artnum><issn>1866-7511</issn><eissn>1866-7538</eissn><abstract>Since the micro-resistivity imaging logging tool cannot achieve 360° full coverage imaging around the well, there will be interval blank zone, resulting in the missing information of geology. In order to measure the size of gravels from the images, this paper adopts the ordinary kriging interpolation method to interpolate the missing images to restore the blank zone and then uses the automatic characterization method to measure the size of gravels on the restored images. The results show that the method can not only restore the outline and characteristics of the gravels in the blank zone and fill in the missing parts of the image effectively, but also measure the gravel grain size from the restored logging image directly, which greatly reduces the manual measurement workload. As well, there is slight difference between the measured size and the actual size of the gravels. This method can be applied to the automatic quantification of gravel grain size in uncored well sections, which will provide fine information for basic geological research in whole well.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s12517-021-07866-x</doi></addata></record> |
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| subjects | Earth and Environmental Science Earth science Earth Sciences Electrical resistivity Geology Grain size Gravel Image restoration Imaging techniques Kriging interpolation Logging Original Paper Particle size Statistical methods |
| title | Automatic calculating grain size of gravels based on micro-resistivity image of well |
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