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Objective based geochemical anomaly detection—Application of discriminant function analysis in anomaly delineation in the Kuh Panj porphyry Cu mineralization (Iran)


Parisa Roshani, Ahmad Reza Mokhtari, Seyed Hasan Tabatabaei


A common objective method for anomaly detection in geochemical exploration is target delineation by discriminant function analysis. Discriminant analysis (DA) is a multivariate statistical technique that classifies each observation into a specific group based on observed predictor variables and predefined groups. In the present study a new approach is considered for geochemical anomaly identification employing DA and “real” pre-defined “anomaly” and “background” data set. The anomalous and background samples are identified based on presence or absence of mineralization in depth; so, this method is introduced as “objective approach”. In order to classify surface geochemical samples into anomaly and background, assays of core drillings in the Kuh Panj porphyry Cu mineralization are used. They are classed as anomaly if the presence of mineralization is proven and are labeled as background if the …

Journal Papers

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