Mahyar Yousefi; Samaneh Barak; Amir Salimi; Saeed Yousefi
Abstract
In this paper, we discuss the concepts behind dispersion patterns of geochemical anomalies when applied for prospecting mineral deposits in different exploration scales. The patterns vary from regional to local scale geochemical surveys, which is due to the differences in the corresponding underlying ...
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In this paper, we discuss the concepts behind dispersion patterns of geochemical anomalies when applied for prospecting mineral deposits in different exploration scales. The patterns vary from regional to local scale geochemical surveys, which is due to the differences in the corresponding underlying processes. Thus the ways for modelling the dispersion patterns and driving significant geochemical signatures should consider the variety when the area under study are delimited from regional to deposit scales exploration. Subsequently, this paper faces with two questions, namely (1) should various geochemical indicators be integrated in different exploration scales aiming at introducing stronger signatures of mineral deposits? and (2) how does the exploration scale affect dispersion patterns of geochemical indicator elements? We demonstrate that the exploration scale plays an important role on the reliability and usefulness of geochemical anomaly models. In this regard, although fusion may achieve reputable outcomes at regional scale exploration, we demonstrate that integration doesn’t gain accurate results for exploration at local scale, which is due to the diversities of the elemental distributions in the two different scales. This achievement is approved by comparing two geochemical signatures, one obtained by integration of two different indicator factors and the other one that used a single factor. The former produces almost the whole studied area as prospective, while the later recognizes ~10% of the area for further exploration, which is closely related to the porphyry Cu mineralization and is verified by drilling results.
Hossein Mahdiyanfar; Amir Salimi
Abstract
This work aims to investigate the geochemical signatures of the Cu porphyry deposit in the Dalli area using the geochemical soil samples. At the first step, the geochemical data was opened using the Centered Log-Ratio (CLR) transform method. Then those outlier samples that reduce the accuracy of the ...
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This work aims to investigate the geochemical signatures of the Cu porphyry deposit in the Dalli area using the geochemical soil samples. At the first step, the geochemical data was opened using the Centered Log-Ratio (CLR) transform method. Then those outlier samples that reduce the accuracy of the geochemical models were detected and removed using the Mahalanobis Distance (MD) method. We applied the Principal Component Analysis (PCA) and Geochemical Mineralization Prospectivity Index (GMPI) methods on the cleaned transformed geochemical dataset. The PCA method identified five principal components (PCs), from which PC1 including Cu, Au, and Mo, are specified as the mineralization factor (MF). The GMPI approach can improve the multivariate geochemical signature in geochemical mapping. Hence, the GMPI values of the samples were calculated based on the score values of MF (Cu, Au, Mo). The results convey that the large values of GMPI (MF) (Cu, Au, Mo) strongly correlate with the quartz diorite porphyry rocks and potassic alteration zones. The GMPI (MF (Cu, Au, Mo)) index was modeled using the Concentration-Number (C-N) fractal method. The C-N fractal model identified four geochemical populations based on the different fractal dimensions. The geochemical anomaly map of GMPI (MF) (Cu, Au, Mo) was delineated using these classified populations. The obtained promising areas were validated adequately by more detailed exploration works and deep drilled boreholes as well. The Cu-Au mineralization potential parts are appropriately mapped by this hybrid method. The results obtained demonstrate that this scenario can be adequately used for geochemical mapping on local scales.
