A Multivariate Geochemical Investigation of Borehole Samples for Gold Deposits Exploration
— The aim of this paper is to carry out a geochemical multivariate analysis on Qolqola gold deposit which is located in Kordestan province of Iran. The analysis and interpretation of geochemical data was carried out based on the results of 543 drilling core samples analyzed for Cu, Pb, W, Mo, Ag, As...
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Veröffentlicht in: | Geochemistry international 2020, Vol.58 (1), p.40-48 |
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The aim of this paper is to carry out a geochemical multivariate analysis on Qolqola gold deposit which is located in Kordestan province of Iran. The analysis and interpretation of geochemical data was carried out based on the results of 543 drilling core samples analyzed for Cu, Pb, W, Mo, Ag, As, Bi, Hg and Au. The purpose of this paper is to use probability plot modeling method for anomaly separation and data classification. For this purpose, three sub-population from Au probability plot modeling was recognized and the thresholds obtained and labeled with the codes 0, 1, and 2 after modeling (code 0: Au < 60 ppb as background, code 1: 60 ppb < Au < 870 ppb as geochemical halo and code 2: Au > 870 ppb as anomaly range). The rearranged data set was used to evaluate discriminant function method. The results were introduced Ag, Hg, Sb, W and Pb as variables related to the mineralization event. The stepwise method was reduced the important variables as Au, Ag, As, W and Bi. Base on the exploration information from the study area, variables such as Ag, As, Sb, Hg, W, Pb were considered as variables were affected by Au mineralization event. |
doi_str_mv | 10.1134/S0016702920010103 |
format | Article |
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The aim of this paper is to carry out a geochemical multivariate analysis on Qolqola gold deposit which is located in Kordestan province of Iran. The analysis and interpretation of geochemical data was carried out based on the results of 543 drilling core samples analyzed for Cu, Pb, W, Mo, Ag, As, Bi, Hg and Au. The purpose of this paper is to use probability plot modeling method for anomaly separation and data classification. For this purpose, three sub-population from Au probability plot modeling was recognized and the thresholds obtained and labeled with the codes 0, 1, and 2 after modeling (code 0: Au < 60 ppb as background, code 1: 60 ppb < Au < 870 ppb as geochemical halo and code 2: Au > 870 ppb as anomaly range). The rearranged data set was used to evaluate discriminant function method. The results were introduced Ag, Hg, Sb, W and Pb as variables related to the mineralization event. The stepwise method was reduced the important variables as Au, Ag, As, W and Bi. Base on the exploration information from the study area, variables such as Ag, As, Sb, Hg, W, Pb were considered as variables were affected by Au mineralization event.</description><identifier>ISSN: 0016-7029</identifier><identifier>EISSN: 1556-1968</identifier><identifier>DOI: 10.1134/S0016702920010103</identifier><language>eng</language><publisher>Moscow: Pleiades Publishing</publisher><subject>Antimony ; Bismuth ; Boreholes ; Copper ; Core drilling ; Cores ; Coring ; Discovery and exploration ; Drilling ; Earth and Environmental Science ; Earth Sciences ; Exploration ; Geochemistry ; Gold ; Gold industry ; Lead ; Mercury ; Mercury (metal) ; Mineralization ; Modelling ; Multivariate analysis ; Probability theory ; Silver</subject><ispartof>Geochemistry international, 2020, Vol.58 (1), p.40-48</ispartof><rights>Pleiades Publishing, Ltd. 2020</rights><rights>COPYRIGHT 2020 Springer</rights><rights>2020© Pleiades Publishing, Ltd. 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a378t-b2c9b28b250fa817b3493f9512d4814ce93b195bc4b5e94454c0d1bdb0fac44d3</citedby><cites>FETCH-LOGICAL-a378t-b2c9b28b250fa817b3493f9512d4814ce93b195bc4b5e94454c0d1bdb0fac44d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1134/S0016702920010103$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1134/S0016702920010103$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Moradpouri, F.</creatorcontrib><creatorcontrib>Ghavami-Riabi, R.</creatorcontrib><title>A Multivariate Geochemical Investigation of Borehole Samples for Gold Deposits Exploration</title><title>Geochemistry international</title><addtitle>Geochem. Int</addtitle><description>—
The aim of this paper is to carry out a geochemical multivariate analysis on Qolqola gold deposit which is located in Kordestan province of Iran. The analysis and interpretation of geochemical data was carried out based on the results of 543 drilling core samples analyzed for Cu, Pb, W, Mo, Ag, As, Bi, Hg and Au. The purpose of this paper is to use probability plot modeling method for anomaly separation and data classification. For this purpose, three sub-population from Au probability plot modeling was recognized and the thresholds obtained and labeled with the codes 0, 1, and 2 after modeling (code 0: Au < 60 ppb as background, code 1: 60 ppb < Au < 870 ppb as geochemical halo and code 2: Au > 870 ppb as anomaly range). The rearranged data set was used to evaluate discriminant function method. The results were introduced Ag, Hg, Sb, W and Pb as variables related to the mineralization event. The stepwise method was reduced the important variables as Au, Ag, As, W and Bi. Base on the exploration information from the study area, variables such as Ag, As, Sb, Hg, W, Pb were considered as variables were affected by Au mineralization event.</description><subject>Antimony</subject><subject>Bismuth</subject><subject>Boreholes</subject><subject>Copper</subject><subject>Core drilling</subject><subject>Cores</subject><subject>Coring</subject><subject>Discovery and exploration</subject><subject>Drilling</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Exploration</subject><subject>Geochemistry</subject><subject>Gold</subject><subject>Gold industry</subject><subject>Lead</subject><subject>Mercury</subject><subject>Mercury (metal)</subject><subject>Mineralization</subject><subject>Modelling</subject><subject>Multivariate analysis</subject><subject>Probability theory</subject><subject>Silver</subject><issn>0016-7029</issn><issn>1556-1968</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp1kD1PwzAQhi0EEqXwA9gsMaf4M4nHUkqpVMRQWFgi23FaV2kc7LSCf49DkBgQuuFOd-9zXwBcYzTBmLLbNUI4zRARJAbR6AkYYc7TBIs0PwWjvpz09XNwEcIOIcaoyEbgbQqfDnVnj9Jb2Rm4ME5vzd5qWcNlczShsxvZWddAV8E7583W1Qau5b6tTYCV83Dh6hLem9YF2wU4_2hr57-JS3BWyTqYqx8_Bq8P85fZY7J6Xixn01UiaZZ3iSJaKJIrwlElc5wpygStBMekZDlm2giqsOBKM8WNYIwzjUqsShXlmrGSjsHN0Lf17v0QNy527uCbOLIglFPECU1JVE0G1UbWprBN5TovdbSyv9Y1prIxP80I4lnOKIoAHgDtXQjeVEXr7V76zwKjov958efnkSEDE6K22Rj_u8r_0Bc8NYJ4</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Moradpouri, F.</creator><creator>Ghavami-Riabi, R.</creator><general>Pleiades Publishing</general><general>Springer</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>L.G</scope></search><sort><creationdate>2020</creationdate><title>A Multivariate Geochemical Investigation of Borehole Samples for Gold Deposits Exploration</title><author>Moradpouri, F. ; Ghavami-Riabi, R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a378t-b2c9b28b250fa817b3493f9512d4814ce93b195bc4b5e94454c0d1bdb0fac44d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Antimony</topic><topic>Bismuth</topic><topic>Boreholes</topic><topic>Copper</topic><topic>Core drilling</topic><topic>Cores</topic><topic>Coring</topic><topic>Discovery and exploration</topic><topic>Drilling</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Exploration</topic><topic>Geochemistry</topic><topic>Gold</topic><topic>Gold industry</topic><topic>Lead</topic><topic>Mercury</topic><topic>Mercury (metal)</topic><topic>Mineralization</topic><topic>Modelling</topic><topic>Multivariate analysis</topic><topic>Probability theory</topic><topic>Silver</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Moradpouri, F.</creatorcontrib><creatorcontrib>Ghavami-Riabi, R.</creatorcontrib><collection>CrossRef</collection><collection>Aqualine</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>Geochemistry international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Moradpouri, F.</au><au>Ghavami-Riabi, R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Multivariate Geochemical Investigation of Borehole Samples for Gold Deposits Exploration</atitle><jtitle>Geochemistry international</jtitle><stitle>Geochem. Int</stitle><date>2020</date><risdate>2020</risdate><volume>58</volume><issue>1</issue><spage>40</spage><epage>48</epage><pages>40-48</pages><issn>0016-7029</issn><eissn>1556-1968</eissn><abstract>—
The aim of this paper is to carry out a geochemical multivariate analysis on Qolqola gold deposit which is located in Kordestan province of Iran. The analysis and interpretation of geochemical data was carried out based on the results of 543 drilling core samples analyzed for Cu, Pb, W, Mo, Ag, As, Bi, Hg and Au. The purpose of this paper is to use probability plot modeling method for anomaly separation and data classification. For this purpose, three sub-population from Au probability plot modeling was recognized and the thresholds obtained and labeled with the codes 0, 1, and 2 after modeling (code 0: Au < 60 ppb as background, code 1: 60 ppb < Au < 870 ppb as geochemical halo and code 2: Au > 870 ppb as anomaly range). The rearranged data set was used to evaluate discriminant function method. The results were introduced Ag, Hg, Sb, W and Pb as variables related to the mineralization event. The stepwise method was reduced the important variables as Au, Ag, As, W and Bi. Base on the exploration information from the study area, variables such as Ag, As, Sb, Hg, W, Pb were considered as variables were affected by Au mineralization event.</abstract><cop>Moscow</cop><pub>Pleiades Publishing</pub><doi>10.1134/S0016702920010103</doi><tpages>9</tpages></addata></record> |
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subjects | Antimony Bismuth Boreholes Copper Core drilling Cores Coring Discovery and exploration Drilling Earth and Environmental Science Earth Sciences Exploration Geochemistry Gold Gold industry Lead Mercury Mercury (metal) Mineralization Modelling Multivariate analysis Probability theory Silver |
title | A Multivariate Geochemical Investigation of Borehole Samples for Gold Deposits Exploration |
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