Mapping of single- and multi-element geochemical indicators based on catchment basin analysis: Application of fractal method and unsupervised clustering models

Abstract

The study aimed to recognize significant single- and multi-elemental geochemical indicators associated with porphyry and skarn copper deposits in the Varzaghan district, NW Iran, from stream sediment geochemical data. In this regard, because of the diversity and complexity of geological processes that influence dispersion patterns of geochemical elements in different areas, sample catchment basin (SCB) modeling of stream sediments was applied. To judge the capability of each single-element geochemical indicator to predict exploration targets of mineral deposits of the type sought, prediction-area plot analysis was employed. Then, concentration-area fractal modeling was performed on the SCB models to delineate geochemical anomalies of each indicator element. Next, a Cu-Au-Mo-Bi association was considered to reflect multi-element indicator of porphyry-skarn Cu mineralization. Different populations of the SCB multi-element geochemical indicators were delineated by three unsupervised clustering methods, namely K-means, K-medoids and fuzzy c-means. Silhouette Width and Xie-Beni validation indices were calculated for selecting the optimal cluster number to optimize delineation of significant anomalies. Finally, for quantitative evaluation of the efficiency of single- and multi-element indicator anomalies in delineating exploration targets, we applied normalized density and success-rate curve based on the known Cu occurrences in the study area.