Comparative analysis between concentration- number (C-N) and concentration- area (C-A) fractal models for separating anomaly from background in Siahrood 100,000 sheet, NW Iran.

Summary
In this paper Concentration-Number (C-N) and Concentration-Area (C-A) fractal models were used for separating anomaly from background for Cu, Mo, Fe2O3 and Sb in Siahrood 1:100,000 sheet, NW Iran. First, 1238 stream sediment samples were taken and analyzed. Then, the threshold values were obtained for anomaly separation from the log- log plots. The log–log plots can be divided into three segments or phases that correlate with lithological formation, faults and alteration in the study area. Using the results of fractal modelling, the anomaly maps were drawn and anomalous areas were identified. Elemental anomaly maps resulted from the C-A and C- N fractal models were compared withthe locations of mineralization/deposits in the study area.Results showed thatthere was a good correlation between the locations of mineralization/deposits and anomaly region for both fractal models. But the concentration-area fractal model could hit more mineralization/deposits. This is more obvious for Cu. Results also showed that most of the Cu, Fe and Mo anomalies located in igneous rocks, altered igneous rocks and faults. Because of activity of hydrothermal solutions in intrusive rocks in the northern part of the study area and volcanic rocks in central parts, intrusive and volcanic rocks, altered and quartzite veins, and mineralization zones occur.
 
Introduction
Delineation of anomalies from background is an essential task in geochemical exploration. Geochemical data are usually characterized by their spatial positions, meaning that elemental concentration varies spatially. The concentration–area model (C–A model) has been developed and applied by many geoscientists. Another useful model for separating anomaly from background is the number–size model (N–S model), which has been widely used by many geoscientists.
 
Methodology and Approaches
Concentration-number and concentration-area fractal models were used for separating anomaly from background. Then with drawingthe log-log elemental plot the threshold values obtained for anomaly separation. Using the results of fractal modelling the anomaly maps were drawn and anomaly regions were identified. Elemental anomaly maps resulted from the concentration-area and concentration- number fractal models were compared withthe locations of mine indexes in the study area.
 
Results and Conclusions
Results showed thatthere was a good correlation between the locations of mine indexes and anomaly region for both fractal models. In other words most of anomalies derived from C-A and N-S models hits mine indexes in the region. But the concentration-area fractal model hit more mine indexes. This is more obvious for Cu. Results also showed that most of the Cu, Fe and Mo anomalies located in igneous rocks, altered igneous rocks and faults.