Identification of Mineralization in Geochemistry Along a Transect Based on the Spatial Curvature of Log-Ratios

A Method to Identify Geochemical Mineralization on Linear Transects

“…As already indicated in the introduction, the main idea of the methodology developed in Mikšová et al (2019b) is that at the beginning and end of a transect crossing a potential mineralization, important log-ratios of an element pair display a very quick spatial change which can be captured by a measure based on the curvature of the latter.…”

“…A further argument for considering (log-)ratios is the assumption that there could be elements which are stable and thus not affected by a mineralization, and others are very indicative of mineralized zones. The log-ratio of such elements could even better express the local change around a mineralization, because measurement and analysis uncertainties could cancel each other out (Mikšová et al, 2019b).…”

“…On the other hand, D m different elements would lead to D m (D m −1)/2 different (and relevant) pairwise log-ratios, which makes a visual inspection practically impossible. For this reason, Mikšová et al (2019b) have introduced a procedure to rank the list of log-ratio pairs according to their ability to indicate mineralization. This is done by first approximating the individual element concentration by a smooth fit, taking log-ratios of the smooth fits, and computing a measure of curvature.…”

“…In this paper we briefly review the method of Mikšová et al (2019b). Then we apply this procedure to two geochemical data sets, originating from surveys carried out in Greenland and France, respectively, in the frame of the ongoing project "UpDeep" (UpDeep, 2017(UpDeep, -2020, which aims at developing and implementing a methodology to identify mineralization.…”

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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 et al (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.

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