Abstract

Stream sediments are the preferred sampling method in regional geochemical exploration for Au deposits in regions displaying well-defined drainage systems. Analysis of either bulk leach extractable gold (BLEG) and aqua regia-extractable multi-element analysis of fine fraction sediments are two common analytical approaches. This study examines the efficiency of detecting known ore deposits and prospects using parametric (Q-Q) and nonparametric (U-spatial and C-A fractal) modeling of a large compilation of company stream sediment and rock chip geochemical data from exploration programs in the Eastern Black Sea region of Turkey, to identify geochemical patterns related to major precious and base metal deposits.The median and 95th percentile values for Au are similar across the different lithological groups, although BLEG values are high in granite and volcanic-dominated terranes. In general, C-A and U-spatial modeling of individual elements concentrations and PCA scores were more effective than Q-Q plots in separating populations associated with the effects of mineralization and delivered lower estimates for thresholds to the dominant “background” population. There is strong spatial association between the anomalous geochemical populations (especially for PCA scores) and the locations of the majority of known Au ± Ag and Cu ± Pb ± Zn deposits in the study area. Most of the known Au mineral deposits occur in catchments with marginal to strongly anomalous Au concentrations in BLEG or the <180 μm fraction. Known Pb and Cu deposits (of various genetic types) are generally contained in catchments displaying the third or higher C-A fractal or U-spatial populations. BLEG was marginally more effective than <180 μm in detecting catchments with known mineralization.

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