L. D. Andriashek

The differentiation of sample media types and mineralization from multi-element geochemistry using multivariate methods and digital topography

Multi-element geochemical data can be effectively interpreted through the application of multivariate statistical techniques, imaging methods and integration with digital topographic information. These techniques have been applied to a suite of 1665 soil samples collected in a sampling program from the central Sumatra area of Indonesia. The selected samples were analyzed for Au, Cu, Pb, Zn, As, Sb, Ba, Ca, Cd, Co, Cr, Fe, Ga, K, La, Li, Mg, Mn, Nb, Ni, Sc, Sr, Ti, V, Y, Zr and Hg using aqua-regia digestion followed by ICP–IES determination. Plan maps of individual elements proved difficult to interpret with several elements displaying bimodal populations. The spatial patterns of individual elements appeared to be discontinuous and raised suspicion that the bimodal population reflected differences in sample media rather than features related to lithology or mineralization. Statistical methods were employed to test the hypothesis of differences in sample media types. Principal components analysis identified several distinct element associations and populations. The scores of the samples for each principal component were interpolated, imaged and plotted as plan maps. The first principal component was difficult to interpret in plan view and did not appear to reflect any lithological or known mineralization trends. It was concluded that the patterns associated with the first component may reflect differences...

Learn More