Principal component analysis and K-means clustering as tools during exploration for Zn skarn deposits and industrial carbonates, Sala area, Sweden

Abstract

This contribution presents an application of principal component analysis (PCA) and K-means clustering as tools for data dimension reduction and grouping of multivariate, whole-rock lithogeochemical data. The study dataset consists of 64 geochemical variables and measurements of spectrophotometric brightness determined from 181 dolomite marble samples, collected at various distance from two contrasting types of mineral deposits, 1) stratabound, dolomite marble- and skarn-hosted Zn-Pb-Ag sulphide deposits and 2) industrial dolomite deposits. Clustering and PCA outputs are assessed based on spatial distribution relative to known mineral deposits and interpretability using geological domain knowledge, to test if the methods can provide a non-biased classification of dolomite samples which is useful for exploration vectoring. The PCA illustrate that three principle components derived from centered log-ratio transformed data can account for 79.69% of the dataset variance. K-means clustering provide unsupervised division of samples into different groups reflecting relative contents of detrital (siliciclastic-volcaniclastic), biogenic and hydrothermal components in the marble protoliths. Spatial analysis of principal components and K-means clusters reveal systematic distribution patterns relative to known deposits, thus providing an exploration guide. The samples most prospective for Zn-Pb-Ag deposits are divided into groups of ‘halo dolomite’ exhibiting elevated Fe and Mn, and an ‘ore dolomite’ also showing elevated Zn, Pb, Ag, Sb, Hg. This can be reconciled with magnetite and Mn-bearing Mg-silicates and carbonates in hydrothermal alteration haloes, and proximal enrichment in hydrothermal sulphides (galena, pyrrhotite, pyrite, sphalerite). Samples in these groups returned low spectrophotometric brightness, resulting from sulphides and Fe oxides grinding to dark powders during sample preparation, significantly lowering the brightness of powdered dolomite marble, even when occurring in low concentrations. Conversely, a ‘clean dolomite’ group is characterized by low contents of the elements above, high contents of Ca, Mg, Sr and total carbon, low magnetic susceptibility and high spectrophotometric brightness, and spatially coincide with known industrial dolomite deposits. An additional group of ‘detrital-rich dolomite’ is distinct from the other groups in an elevated content of high field strength elements and Al, and intermediate spectrophotometric brightness. This variety represent samples containing a higher content of co-settled volcaniclastic-siliciclastic material in the marble precursor. Assessment of the clustered data in relation to magnetic susceptibility measurements from the same samples show that Halo and Ore dolomite can be differentiated from other dolomite types by geomagnetic methods, hence providing a proxy for their indirect detection during geophysical surveys.