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A Method to Identify Geochemical Mineralization on Linear Transects

Authors :
Dominika Mikšová
Christopher Rieser
Peter Filzmoser
Simon Mose Thaarup
Jeremie Melleton
Source :
Austrian Journal of Statistics, Vol 49, Iss 4 (2020)
Publication Year :
2020
Publisher :
Austrian Statistical Society, 2020.

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 Filzmoser (2019b) have introduced a method for the identification of spatial patterns with increased element concentrations in samples along a linear sampling transect. This procedure 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 mineralization. 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.

Details

Language :
English
ISSN :
1026597X
Volume :
49
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Austrian Journal of Statistics
Publication Type :
Academic Journal
Accession number :
edsdoj.9616369be0942f98ab6d861244625c0
Document Type :
article
Full Text :
https://doi.org/10.17713/ajs.v49i4.1133