The use of multi-element geochemistry is becoming increasingly prevalent in exploration. With tools such as portable X-ray fluorescence (pXRF) now a staple in many geologists’ toolkits, multi-element geochemistry is more accessible than ever. As inductively coupled plasma mass spectrometry (ICP-MS) is available at most laboratories, reliable low-level multi-element geochemical analyses are routinely conducted on samples ranging from early-stage soil surveys to diamond drill core. However, in many cases, only one or two of the dozens of reported elements are used for targeting, leaving a wealth of potentially informative data overlooked. This unused data can provide critical insight into key aspects of a mineral deposits, from fingerprinting to lithological and alteration discrimination.
Interpreting geochemical data is a methodical process, and developing a clear understanding of the dataset is the essential first step. Exploratory Data Analysis (EDA) involves extracting as much as possible from the complete dataset. This step helps determine which pre-processing methods, such as using central log ratios among others, are required before further manipulation and presentation for interpretation.
Understanding how elements interact with one another is the next major step. Correlations between elements can be identified using tools such as correlation matrices and principal component analysis (PCA). By recognising these relationships, geologists can perform deposit fingerprinting. A simple example is the well-established correlation between arsenic and silver with gold in orogenic deposits.
Geochemistry can be used to vector exploration targets effectively. Common trace-element ratios such as vanadium to scandium (V/Sc) and strontium to yttrium (Sr/Y) can help identify potentially favourable magmas associated with porphyry copper deposits. Additionally, scatter plots of immobile elements such as Thorium, Scandium and Titanium enable lithological discrimination, providing a quick and effective means of validating core logging. Alteration minerals and their interrelationships can also be characterised through geochemical data, including proportions of sericite to chlorite and biotite, feldspar composition, and the degree of sulfidation. Geochemistry has also been a vital tool in identifying lithium pegmatites. By using various elemental signatures, their fertility and classification can be determined without requiring lithium assays, which are often absent from historical datasets.
Additionally, by using advance tools such as Uniform Manifold Approximation and Projection for Dimension Reduction (UMAP) and ternary PCA maps, geochemistry can be integrated with other datasets, such as remote sensing and airborne geophysics, to produce desktop-based geological maps for field validation. These techniques can also be applied to historical soil-sample data, even when only a limited number of elements have been assayed.
