Seyyed saeed Ghannadpour - Department of Mining Engineering, Amirkabir University of Technology (Tehran Polytechnic)
Ardeshir Hezarkhani - Department of Mining Engineering, Amirkabir University of Technology (Tehran Polytechnic)

Undoubtedly, determining the threshold of anomalies and separating geochemical anomalies from background is one of the most important stages of minerals exploration. In the discussion of the separation of geochemical anomalies from background, there are different methods that structural methods have shown much greater efficiency than nonstructural methods. Among structural methods (methods that consider the position and location of samples), U-statistic and fractal methods have a special place. In this study, by using the algorithm of the abovementioned methods and combining them, a new method as U values fractal model (U-N and U-A) is introduced for the first time. Then, the proposed method is employed to determine the boundaries of background and anomalous populations (about the gold (Au) and arsenic (As) elements in Susanvar district). Results show that in U-N and U-A fractal models, the first fracture boundary is much clearer and more accurate than previous fractal models (C-N and C-A) in the same condition. In U-N model, due to the nature of the U method algorithm, there is a discontinuity as the exact threshold between background and anomaly that in U-A model, this does not exist due to the homogenization of U values. In this method, the exact threshold between background and anomaly is determined by the U-statistic method and by its combination with the fractal method, in each population, sub-populations are identified more accurately and simply than the concentration fractal model. Finally, a lithogeochemical map of the study area is provided for Au and As which has been prepared using U-N and U-A fractal methods. In these maps (especially the prepared maps by U-A model), the delineated Au-As mineralization is closely associated with the defined Au ore indications in the study area.

Anomalies Delineation, Susanvar, U-Statistics, U-N, U-A fractal