Identification of mineralization features and deep geochemical anomalies using a new FT-PCA approach

The analysis of geochemical data in frequency domain, as indicated in this research study, can provide new exploratory informationthat may not be exposed in spatial domain. To identify deep geochemical anomalies, sulfide zone and geochemical noises in Dalli Cu–Au porphyry deposit, a new approach based on coupling Fourier transform (FT) and principal component analysis (PCA) has beenused. The relationship between frequency attributes of surface geochemical data and mineralizing depth has been discussed. Todetermine the exploratory features in different frequencies, high- and low-pass filters have been performed on frequency domain; PCAmethod has been employed on these frequency bands separately. The results of this study have identified the mineralizing elements andshowed the relationship between high- and low-frequencies and depths of anomalies. The geochemical halos of mineral deposits atdifferent depths affected frequency distribution of elements in the surface. The information obtained from geophysical studies andexploration drillings, such as, trenches and boreholes, confirm the results of FT–PCA method. This new approach is very effective toolto identify the promising anomalies and deep mineralization without drilling.