Accounting for Secondary Variable for the Classification of Mineral Resources using Cokriging Technique; a Case Study of Sarcheshmeh Porphyry Copper Deposit
Due to substantial effect of classification of resource models on future mine planning, one should come with an accurate method of estimation to guarantee that the minimum error is acquired in the estimation process. The known world class Cu-Mo deposit, Sarcheshmeh Porphyry deposit (central Iran) se...
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| Format: | Article |
| Language: | English |
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University of Tehran
2012-12-01
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| Series: | International Journal of Mining and Geo-Engineering |
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| Online Access: | http://ijmge.ut.ac.ir/article_30517_3b8df6ecea2a9e2fd7cd7c44dcd1eeb2.pdf |
| _version_ | 1818910274224128000 |
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| author | Hassan Rezaee Omid Asghari |
| author_facet | Hassan Rezaee Omid Asghari |
| author_sort | Hassan Rezaee |
| collection | DOAJ |
| description | Due to substantial effect of classification of resource models on future mine planning, one should come with an accurate method of estimation to guarantee that the minimum error is acquired in the estimation process. The known world class Cu-Mo deposit, Sarcheshmeh Porphyry deposit (central Iran) selected as the study area. The Hypogene zone of the deposit was chosen as the space in which estimation processes should be done. The mean value of Molybdenum and Copper extracted from the top part of this zone, where sampling operations have been done on a dense grid. The correlation coefficient of 0.45 allowed going through the process of interpolation. It was shown that taking account Cu as an auxiliary variable the interpolation process, the estimation had been improved. Simple Cokriging interpolation technique is applied and it was proved that using Cu, with mean value of 0.61 percent, as secondary variable will decrease the estimation variance of Mo interpolation which has the mean value of 0.022 percent. The chief influence of this reduction appeared when the resource should be classified. Only 1% decrease was obtained when Cu used as secondary variable, but in an industrial aspect it can be of great importance as a high number of voxels in “Indicated” class changed into “Measured” one. This led to 133 Mt more Mo-ore that were added to the previous “Measured” class blocks. Also, the transition zones where the changes in class of cells have occurred are identified; these zones are mainly the places where Mo has fewer samples than Cu. |
| first_indexed | 2024-12-19T22:40:12Z |
| format | Article |
| id | doaj.art-c8301867138d4bd9917070227f9c30f2 |
| institution | Directory Open Access Journal |
| issn | 2345-6930 2345-6949 |
| language | English |
| last_indexed | 2024-12-19T22:40:12Z |
| publishDate | 2012-12-01 |
| publisher | University of Tehran |
| record_format | Article |
| series | International Journal of Mining and Geo-Engineering |
| spelling | doaj.art-c8301867138d4bd9917070227f9c30f22022-12-21T20:03:06ZengUniversity of TehranInternational Journal of Mining and Geo-Engineering2345-69302345-69492012-12-01461678030517Accounting for Secondary Variable for the Classification of Mineral Resources using Cokriging Technique; a Case Study of Sarcheshmeh Porphyry Copper DepositHassan Rezaee0Omid Asghari1M.Sc. student of Mining Engineering, School of Mining, College of Engineering, University of Tehran, IranAssistant Professor, School of Mining, College of Engineering, University of Tehran, IranDue to substantial effect of classification of resource models on future mine planning, one should come with an accurate method of estimation to guarantee that the minimum error is acquired in the estimation process. The known world class Cu-Mo deposit, Sarcheshmeh Porphyry deposit (central Iran) selected as the study area. The Hypogene zone of the deposit was chosen as the space in which estimation processes should be done. The mean value of Molybdenum and Copper extracted from the top part of this zone, where sampling operations have been done on a dense grid. The correlation coefficient of 0.45 allowed going through the process of interpolation. It was shown that taking account Cu as an auxiliary variable the interpolation process, the estimation had been improved. Simple Cokriging interpolation technique is applied and it was proved that using Cu, with mean value of 0.61 percent, as secondary variable will decrease the estimation variance of Mo interpolation which has the mean value of 0.022 percent. The chief influence of this reduction appeared when the resource should be classified. Only 1% decrease was obtained when Cu used as secondary variable, but in an industrial aspect it can be of great importance as a high number of voxels in “Indicated” class changed into “Measured” one. This led to 133 Mt more Mo-ore that were added to the previous “Measured” class blocks. Also, the transition zones where the changes in class of cells have occurred are identified; these zones are mainly the places where Mo has fewer samples than Cu.http://ijmge.ut.ac.ir/article_30517_3b8df6ecea2a9e2fd7cd7c44dcd1eeb2.pdfSimple Co-KrigingSecondary VariableEstimation VariancePorphyry Copper DepositResource Classification |
| spellingShingle | Hassan Rezaee Omid Asghari Accounting for Secondary Variable for the Classification of Mineral Resources using Cokriging Technique; a Case Study of Sarcheshmeh Porphyry Copper Deposit International Journal of Mining and Geo-Engineering Simple Co-Kriging Secondary Variable Estimation Variance Porphyry Copper Deposit Resource Classification |
| title | Accounting for Secondary Variable for the Classification of Mineral Resources using Cokriging Technique; a Case Study of Sarcheshmeh Porphyry Copper Deposit |
| title_full | Accounting for Secondary Variable for the Classification of Mineral Resources using Cokriging Technique; a Case Study of Sarcheshmeh Porphyry Copper Deposit |
| title_fullStr | Accounting for Secondary Variable for the Classification of Mineral Resources using Cokriging Technique; a Case Study of Sarcheshmeh Porphyry Copper Deposit |
| title_full_unstemmed | Accounting for Secondary Variable for the Classification of Mineral Resources using Cokriging Technique; a Case Study of Sarcheshmeh Porphyry Copper Deposit |
| title_short | Accounting for Secondary Variable for the Classification of Mineral Resources using Cokriging Technique; a Case Study of Sarcheshmeh Porphyry Copper Deposit |
| title_sort | accounting for secondary variable for the classification of mineral resources using cokriging technique a case study of sarcheshmeh porphyry copper deposit |
| topic | Simple Co-Kriging Secondary Variable Estimation Variance Porphyry Copper Deposit Resource Classification |
| url | http://ijmge.ut.ac.ir/article_30517_3b8df6ecea2a9e2fd7cd7c44dcd1eeb2.pdf |
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