Got soil geochemistry? Want to get beyond a simple single-element map and to normalise for rock type / sample media? We can help you to extract as much value as possible from your soil geochemistry dataset.


Mapping lithology and targeting

  • Objective classification of lithology, alteration or mineralisation from geochemical data.
  • Examine relationships between multiple elements simultaneously.
  • Rapid assessment of trends within the data that may not be apparent with single- or two-element plots.
  • Groupings can inform lithology mapping, exploration targeting, and alteration mapping.

Principal components analysis of 14-element geochemical soil sample dataset, from Marirongoe, Mozambique, groupings informed by Bayesian clustering algorithm. Eigenvectors (arrows) indicate elements influencing the analysis (modified after Sterk et al., 2018).

Map of soil samples from the Marirongoe area, Mozambique, coloured by clusters from the principal components analysis, showing areas of cohesive chemistry, thus mapping variation in lithology (modified after Sterk et al., 2018).