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Detecting subcropping mineralizations but also deeply buried mineralizationsis one important goal in geochemical exploration. The identification of usefulindicators for mineralization is a difficult task as mineralization might beinfluenced by many factors, such as location, investigated media, depth, etc.We propose a statistical method which indicates chemical elements related tomineralization along a transect. Moreover, the method determines along atransect the potential area of the deposit. The identification is based onGeneral Additive Models (GAMs) for the element concentrations across thespatial coordinate(s). The log-ratios of the GAM fits are taken to compute thecurvature, where high and narrow curvature is supposed to indicate themineralization area. By defining a measure for the quantification of highcurvature, the log-ratios can be ranked, and elements can be identified thatare indicative of the anomaly patterns.

Identification of mineralization in geochemistry along a transect based on the spatial curvature of log-ratios