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.

探测地下作物成矿作用以及深埋的成矿作用是地球化学勘探的重要目标之一。确定矿化的有用指标是一项艰巨的任务，因为矿化可能受到许多因素的影响，包括位置，调查的介质和深度。在这里，提出了一种统计方法，该方法指示与沿样线矿化有关的化学元素。此外，该方法确定沿断面的沉积物潜在面积。该识别基于跨空间坐标的元素浓度的通用加性模型（GAM）。GAM拟合的对数比用于计算曲率，其中高曲率和窄曲率被认为指示矿化区域。通过定义量化高曲率的方法，