Geochemical anomaly mapping is a significant method in exploring for Au and associated elements using fine-fraction sediments. The fractal behaviour of geochemical elements has frequently been modelled for geochemical prospectivity mapping. In this study, concentration–area (C-A) and power spectrum–area (S-A) fractal modelling were utilized for Au concentration in stream sediments near the Saqqez mineralization area, NW Iran. A novel integrated approach based on the S-A fractal method and principal component analysis (PCA) was used to improve the geochemical anomaly map. In this approach, the multi-element mineralization factor returned from PCA was modelled by the S-A fractal method, and the obtained results were compared to the C-A and S-A fractal models of the element Au. Six known mineralization zones in the studied area were revisited to validate the fractal models. The elements Au, As, W, and Sb were identified as associated elements based on the log-ratio-transformed data in the shear zone gold mineralization. S-A fractal modelling of the multi-element mineralization factor (SAF-MF) of the Au-associated elements in the mineralization zones enhanced the geochemical halos and increased the prediction rate of mineralization zones using stream sediment geochemical data. The SAF-MF that models the behaviour of frequency signals of associated elements upgraded the geochemical anomaly mapping compared to conventional fractal models.

Supplementary material: Supplementary information including figures S1–S5 is available at https://doi.org/10.6084/m9.figshare.c.6123537

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