Application of geographically weighted regression (GWR) and singularity analysis to identify stream sediment geochemical anomalies, case study, Takab Area, NW Iran

In geologically and lithologically complex areas, distinguishing weak geochemical anomalies from background and defining a valid threshold value are central issues in mineral exploration. This study benefited from using geographically weighted regression (GWR), ordinary least square regression (OLSR), singularity analysis, and a combined model of GWR and singularity analysis to identify geochemical anomalies related to Pb–Zn mineralization in the Takab area (Iran). In the analyses, major oxides were considered independent geo-variables related to upstream of stream sediment samples and on-site rock types. The results of GWR revealed the non-stationary effect of independent geo-variables on Pb–Zn geochemical anomalies, on local R2 among geo-variables, and on measured values of trace elements, which suggested a meaningful improvement in trace element prediction in comparison with OLSR. The results of singularity model showed that geochemical anomalies were closely coincident with known carbonate-hosted Pb–Zn deposits and with carbonaceous geological units in the Takab area. Anomalies delineated by singularity model illustrated another potential for follow-up mineral exploration. The results of the combined model of GWR and singularity model—based on consideration of Type I and Type II errors—exhibited not only higher coincidence with known mineral deposits but also introduced new potential exploration targets in the Takab area; that is, the combined model led to a more profound recognition of weak anomalies in a geologically and lithologically complex area.