Prediction of dispersed mineralization zone in depth using frequency domain of surface geochemical data

Discrimination of the blind and dispersed mineralization deposits is a challenging problem in geochemical exploration. The frequency domain (FD) of the surface geochemical data can solve this important issue. This new exploratory information can be achieved using the interpretation of FD of geochemical data, which is impossible in spatial domain. In this research work, FD of the surface geochemical data is analyzed to decompose the complex geochemical patterns related to the mineral deposits. In order to identify the dispersed mineralization zone in the Chichakloo Pb–Zn deposit, a newly developed approach is proposed based on the coupling of two-dimensional Fourier transform (2DFT) and principal component analysis (PCA). The surface geochemical data is transferred to FD using 2DFT, and two low-pass filters are designed and performed on FD. Then the PCA method is employed on these frequency bands (FBs) separately. This proposed scenario desirably illustrates the relationship between the low frequencies in the surface geochemical distribution map (GDM) and the deep deposits. The informations obtained from the detailed exploration and the exploration drillings such as boreholes confirm the results obtained from this method. This new combined approach is a valuable data-processing tool and pattern-recognition technique in geochemical explorations. This approach is quite inexpensive compared to the traditional exploration methods.

کلیدواژه ها:

Frequency Domain of Geochemical Data ، Principal Component Analysis ، Fourier Transformation ، Dispersed Mineralization Zones ، Pattern Recognition