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 <front>
  <journal-meta>
   <journal-id journal-id-type="publisher-id">Russian Journal of Earth Sciences</journal-id>
   <journal-title-group>
    <journal-title xml:lang="en">Russian Journal of Earth Sciences</journal-title>
    <trans-title-group xml:lang="ru">
     <trans-title>Russian Journal of Earth Sciences</trans-title>
    </trans-title-group>
   </journal-title-group>
   <issn publication-format="online">1681-1208</issn>
  </journal-meta>
  <article-meta>
   <article-id pub-id-type="publisher-id">46933</article-id>
   <article-categories>
    <subj-group subj-group-type="toc-heading" xml:lang="ru">
     <subject>ОРИГИНАЛЬНЫЕ СТАТЬИ</subject>
    </subj-group>
    <subj-group subj-group-type="toc-heading" xml:lang="en">
     <subject>ORIGINAL ARTICLES</subject>
    </subj-group>
    <subj-group>
     <subject>ОРИГИНАЛЬНЫЕ СТАТЬИ</subject>
    </subj-group>
   </article-categories>
   <title-group>
    <article-title xml:lang="en">Investigation of salt plugs intrusion into Dehnow anticline using image processing and geophysical magnetotelluric methods</article-title>
    <trans-title-group xml:lang="ru">
     <trans-title>Investigation of salt plugs intrusion into Dehnow anticline using image processing and geophysical magnetotelluric methods</trans-title>
    </trans-title-group>
   </title-group>
   <contrib-group content-type="authors">
    <contrib contrib-type="author">
     <name-alternatives>
      <name xml:lang="ru">
       <surname>Esmaeil Zadeh</surname>
       <given-names>A </given-names>
      </name>
      <name xml:lang="en">
       <surname>Esmaeil Zadeh</surname>
       <given-names>A </given-names>
      </name>
     </name-alternatives>
     <xref ref-type="aff" rid="aff-1"/>
    </contrib>
    <contrib contrib-type="author">
     <name-alternatives>
      <name xml:lang="ru">
       <surname>Doulati Ardejani</surname>
       <given-names>F </given-names>
      </name>
      <name xml:lang="en">
       <surname>Doulati Ardejani</surname>
       <given-names>F </given-names>
      </name>
     </name-alternatives>
     <xref ref-type="aff" rid="aff-2"/>
    </contrib>
    <contrib contrib-type="author">
     <name-alternatives>
      <name xml:lang="ru">
       <surname>Ziaii</surname>
       <given-names>M </given-names>
      </name>
      <name xml:lang="en">
       <surname>Ziaii</surname>
       <given-names>M </given-names>
      </name>
     </name-alternatives>
     <xref ref-type="aff" rid="aff-3"/>
    </contrib>
    <contrib contrib-type="author">
     <name-alternatives>
      <name xml:lang="ru">
       <surname>Mohammado Khorasani</surname>
       <given-names>M </given-names>
      </name>
      <name xml:lang="en">
       <surname>Mohammado Khorasani</surname>
       <given-names>M </given-names>
      </name>
     </name-alternatives>
     <xref ref-type="aff" rid="aff-4"/>
    </contrib>
   </contrib-group>
   <aff-alternatives id="aff-1">
    <aff>
     <institution xml:lang="ru">  Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran</institution>
     <country>ru</country>
    </aff>
    <aff>
     <institution xml:lang="en">  Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran</institution>
     <country>ru</country>
    </aff>
   </aff-alternatives>
   <aff-alternatives id="aff-2">
    <aff>
     <institution xml:lang="ru">  Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran</institution>
     <country>ru</country>
    </aff>
    <aff>
     <institution xml:lang="en">  Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran</institution>
     <country>ru</country>
    </aff>
   </aff-alternatives>
   <aff-alternatives id="aff-3">
    <aff>
     <institution xml:lang="ru">  Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran </institution>
     <country>ru</country>
    </aff>
    <aff>
     <institution xml:lang="en">  Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran </institution>
     <country>ru</country>
    </aff>
   </aff-alternatives>
   <aff-alternatives id="aff-4">
    <aff>
     <institution xml:lang="ru">  National Iranian Oil Company, Exploration Department, Tehran, Iran</institution>
     <country>ru</country>
    </aff>
    <aff>
     <institution xml:lang="en">  National Iranian Oil Company, Exploration Department, Tehran, Iran</institution>
     <country>ru</country>
    </aff>
   </aff-alternatives>
   <volume>11</volume>
   <issue>3</issue>
   <fpage>1</fpage>
   <lpage>9</lpage>
   <history>
    <date date-type="received" iso-8601-date="2021-11-10T01:57:20+03:00">
     <day>10</day>
     <month>11</month>
     <year>2021</year>
    </date>
   </history>
   <self-uri xlink:href="https://rjes.ru/en/nauka/article/46933/view">https://rjes.ru/en/nauka/article/46933/view</self-uri>
   <abstract xml:lang="ru">
    <p>This paper attempts to consider the results of a magnetotelluric MT geophysical survey and the applicability of image processing method on the TM images of the anticline. The color pixels related to the salt zones have been separated from the other zones from the land surface using image processing method incorporating k-means clustering approach as one of the simplest unsupervised learning algorithms. Field investigations, geological study and the results obtained from the MT survey together with the image processing method identified three salt zones in the study area. These salt zones match well with a decrease in the resistivity of MT data. The application of the proposed method as one of the artificial intelligence technique can be properly used as a cost effective method to identify salt zones from the other areas and preparing a probability map in a regional scale in petroleum exploration.</p>
   </abstract>
   <trans-abstract xml:lang="en">
    <p>This paper attempts to consider the results of a magnetotelluric MT geophysical survey and the applicability of image processing method on the TM images of the anticline. The color pixels related to the salt zones have been separated from the other zones from the land surface using image processing method incorporating k-means clustering approach as one of the simplest unsupervised learning algorithms. Field investigations, geological study and the results obtained from the MT survey together with the image processing method identified three salt zones in the study area. These salt zones match well with a decrease in the resistivity of MT data. The application of the proposed method as one of the artificial intelligence technique can be properly used as a cost effective method to identify salt zones from the other areas and preparing a probability map in a regional scale in petroleum exploration.</p>
   </trans-abstract>
   <kwd-group xml:lang="ru">
    <kwd>Magnetotelluric</kwd>
    <kwd>Dehnow anticline</kwd>
    <kwd>salt plug</kwd>
    <kwd>image processing</kwd>
    <kwd>color pixels</kwd>
    <kwd>cluster</kwd>
   </kwd-group>
   <kwd-group xml:lang="en">
    <kwd>Magnetotelluric</kwd>
    <kwd>Dehnow anticline</kwd>
    <kwd>salt plug</kwd>
    <kwd>image processing</kwd>
    <kwd>color pixels</kwd>
    <kwd>cluster</kwd>
   </kwd-group>
  </article-meta>
 </front>
 <body>
  <p></p>
 </body>
 <back>
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</article>
