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

Detecting subcropping mineralizations but also deeply buried mineralizations is one important goal in geochemical exploration. The identification of useful indicators for mineralization is a difficult task, as mineralization might be influenced by many factors, including location, investigated media and depth. Here, a statistical method is proposed which indicates chemical elements related to mineralization along a transect. Moreover, the method determines the potential area of the deposit along a transect. The identification is based on general additive models (GAMs) for the element concentrations across the spatial coordinate(s). The log-ratios of the GAM fits are taken to compute the curvature, where high and narrow curvature is supposed to indicate the mineralization area. By defining a measure for the quantification of high curvature, the log-ratios can be ranked, and elements can be identified that are indicative of the anomaly patterns.