A method to identify geochemical mineralization on linear transects

Dominika Mikšová, Christopher Rieser, Peter Filzmoser, Simon Mose Thaarup, Jeremie Melleton

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)

Abstract

Mineral exploration in biogeochemistry is related to the detection of anomalies in soil, which is driven by many factors and thus a complex problem. Mikšová, Rieser, and Filz-moser (2019b) have introduced a method for the identification of spatial patterns with increased element concentrations in samples along a linear sampling transect. This proce-dure is based on fitting Generalized Additive Models (GAMs) to the concentration data, and computing a curvature measure from the pairwise log-ratios of these fits. The higher the curvature, the more likely one or both elements of the pair indicate local mineral-ization. This method is applied on two geochemical data sets which have been collected specifically for the purpose of mineral exploration. The aim is to test the technique for its ability to identify pathfinder elements to detect mineralized zones, and to verify whether the method can indicate which sampling material is best suited for this purpose.

Original languageEnglish
Pages (from-to)89-98
Number of pages10
JournalAustrian Journal of Statistics
Volume49
Issue number4
DOIs
Publication statusPublished - 13 Apr 2020

Keywords

  • Curvature
  • Generalized additive models
  • Log-ratios
  • Mineralization

Programme Area

  • Programme Area 4: Mineral Resources

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