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   identification of anomalies using multivariate fractal modeling in the maleksiahkuh region, se iran  
   
نویسنده daya ali akbar ,biabangard habib ,boomeri mohammad
منبع روشهاي تحليلي و عددي در مهندسي معدن - 2024 - دوره : 14 - شماره : 39 - صفحه:13 -25
چکیده    Anomaly separation based on stream sediment data is an important step for mineral exploration. in this article, three methods of cluster analysis, factor analysis and fractal geometry have been used to separate the anomalous and suspected mineralization areas from the background areas. by combining these three methods, a possible mineralization was found in the maleksiahkuh area. in addition, the relationship between the anomalies and the anomaly’s host rocks was discussed. maleksiahkuh is located 35 kilometers north of zahedan and in the eastern part of the flysch zone, iran. multivariate statistical analysis was performed. the results show a positive correlation between copper and molybdenum. the amount of chromium from the field is relatively high. chromium is rich in the host mafic rocks. the presence of large concentrations of chromium in the region can be attributed to the presence of mafic rocks. the highest positive correlation was observed between manganese and cobalt, which is about 0.997. in addition, iron with titanium has a correlation of 0.984. cobalt with iron has a correlation of 0.975. the cluster analysis for the region confirmed the existence of three clusters. the third cluster containing elements as, sr, sn, sb, pb, cu, and ag is probably related to the base-metal mineralization. factor analysis was performed on the elemental concentrations. the sixth factor, which cu and ag elements have the highest weightage, was considered as another mineralization factor. the location of the most concentrated copper in the map derived from the number-size (n-s) fractal method corresponds to the highest score in the factor rating map. there is a good match between copper anomalies and mafic rocks. green crests have always been associated with mineralization, and studies show that there is a good relationship between mineralization and these rocks.
کلیدواژه mineralization ,cluster analysis ,factor analysis ,size(n-s) ,maleksiahkuo
آدرس university of sistan and baluchestan, dept. of mining engineering, iran, university of sistan and baluchestan, dept. of geology, iran, university of sistan and baluchestan, dept. of geology, iran
پست الکترونیکی boomeri@hamoon.usb.ac.ir
 
   identification of anomalies using multivariate fractal modeling in the maleksiahkuh region, se iran  
   
Authors daya ali akbar ,biabangard habib ,boomeri mohammad
Abstract    anomaly separation based on stream sediment data is an important step for mineral exploration. in this article, three methods of cluster analysis, factor analysis and fractal geometry have been used to separate the anomalous and suspected mineralization areas from the background areas. by combining these three methods, a possible mineralization was found in the maleksiahkuh area. in addition, the relationship between the anomalies and the anomaly’s host rocks was discussed. maleksiahkuh is located 35 kilometers north of zahedan and in the eastern part of the flysch zone, iran. multivariate statistical analysis was performed. the results show a positive correlation between copper and molybdenum. the amount of chromium from the field is relatively high. chromium is rich in the host mafic rocks. the presence of large concentrations of chromium in the region can be attributed to the presence of mafic rocks. the highest positive correlation was observed between manganese and cobalt, which is about 0.997. in addition, iron with titanium has a correlation of 0.984. cobalt with iron has a correlation of 0.975. the cluster analysis for the region confirmed the existence of three clusters. the third cluster containing elements as, sr, sn, sb, pb, cu, and ag is probably related to the base-metal mineralization. factor analysis was performed on the elemental concentrations. the sixth factor, which cu and ag elements have the highest weightage, was considered as another mineralization factor. the location of the most concentrated copper in the map derived from the number-size (n-s) fractal method corresponds to the highest score in the factor rating map. there is a good match between copper anomalies and mafic rocks. green crests have always been associated with mineralization, and studies show that there is a good relationship between mineralization and these rocks.
Keywords mineralization ,cluster analysis ,factor analysis ,size(n-s) ,maleksiahkuo
 
 

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