Compositional balance analysis for Cu–Zn(±Co) geochemical anomaly mapping in Trøndelag county, Norway

Abstract

Trøndelag county has been recently the focus of a new mineral exploration wave given its well-known base metal mineralization potential associated with the occurrence of volcanogenic Cu–Zn (±Co ± Ag ± Au) massive sulfide deposits (VMS). This study evaluates a regional low-density soil sampling survey by implementing principal component analysis (PCA), and compositional balance analysis (CoBA) to target prospective areas for base metal mineralization. Principal component analysis indicates a dominant base metal mineralization signature characterized by a correlation between As and Cu–Cr–Co–Ni, which is consistent with the occurrences of mafic metavolcanic and associated low K–Ca metasedimentary rocks. However, several other Cu–Zn occurrences hosted in K- and/or Ca-rich (meta-)sedimentary (e.g., Røros districts) and felsic (meta-)igneous lithologies have been overlooked by this approach. Data- and knowledge-driven balances (i.e., isometric log-ratios) were then constructed to enhance these “weaker” Cu–Zn (±Co) mineralization fingerprints. Most of the data-driven balances (dcobals) are shown to be very noisy, and less useful for base metal geochemical anomaly mapping compared to their more coherent knowledge-driven counterparts (kcobals). However, the kcobals (e.g., for Cu, Zn and Co) highlight relatively large anomalous areas, which makes them less practical if used as individual exploration vectors. To further define zones of economic interest, common anomalous areas (defined as kcobal >75th percentile) have been filtered out from selected kcobal pairs. This has resulted in the identification of several prospective areas that correspond with 15%–20% of the Trøndelag county.This study not only explores the combined use of CoBA and PCA for detecting base metal anomalies, but also elaborates on some factors that can affect the interpretation and performance of multivariate approaches (e.g., mineralization/alteration extension versus survey resolution, geological framework, and deposit type). The visualization and implementation of CoBA presented in this paper aim to improve geoscientists’ understanding of the reach and limitations of using isometric log-ratios for mineral exploration studies.