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 information that 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 been used. The relationship between frequency attributes of surface geochemical data and mineralizing depth has been discussed. To determine the exploratory features in different frequencies, high- and low-pass filters have been performed on frequency domain; PCA method has been employed on these frequency bands separately. The results of this study have identified the mineralizing elements and showed the relationship between high- and low-frequencies and depths of anomalies. The geochemical halos of mineral deposits at different depths affected frequency distribution of elements in the surface. The information obtained from geophysical studies and exploration drillings, such as, trenches and boreholes, confirm the results of FT–PCA method. This new approach is very effective tool to identify the promising anomalies and deep mineralization without drilling.