PROMISING AREA DETECTION USING MULTIVARIATE STATISTICS

Multivariate statistics methods would be able to Analysis so many data simultaneously, therfore the risk of decisions based on these methods will be highly reduced. The exploration Area is lactated in 120 km of Zahedan city. The intrusion of Subplutonic monsodiorite bodies and diorite dikes in sedimentary sequence has made faulting and wide hydrothermal alteration. In a regular grid, 669 samples from the outcrops have been taken. The samples has been analyzed, using ICP-Ms method for Fe, Cu, Cd ,Bi Be ,As ,Ag ,Zn ,W, Te, Sn, Sb, S ,Pb ,Mo and using Fire Assay for Au. The primary data processes revealed element enrichment in some rock outcrops. The most important paragenesis determined using Hierarchical Clustering analysis. The PCA analysis introduces the most important anomalies(PC1). The location of anomalous areas determined with mapping PC1 variable. The importance of anomalies was investigated with the comparison of erosion surface and probable mineraliztion surface. The promising areas for the following Exploration program introduced.