Application of Fourier and wavelet approaches for identification of geochemical anomalies

Abstract

The geochemical data can be transferred to other domains such as frequency and position-scale domains using Fourier transform (FT) and wavelet transform (WT). The investigations made in this paper show the analysis of geochemical data in frequency and position-scale domains can provide new exploratory information that may not be revealed in the spatial domain (SD). The geochemical data of Dalli porphyry deposit (Central Iran) have been examined in SD using principal component analysis (PCA), and as a result, Cu, Au and Mo have been identified as mineralization elements. In this study, to determine the mineralization pattern and identify the new exploration target in Dalli area, FT and WT have been performed on surface geochemical data and then, the obtained data have been analyzed using PCA separately. The results of this analysis on soil geochemical data in frequency domain (FD) have desirably identified the mineralization elements of Au, Cu, Mo and S. In next step, PCA has also been performed on approximate component in one level of position-scale domain, and then, a new index has been presented based on wavelet coefficients, and consequently, significant results have been obtained by PCA of the index. The results of this index have desirably identified the mineralization elements of Au, Cu and Mo unlike the approximate component. Finally, the elements of Au, Cu and Mo have been classified clearly using the combination of mineralization factors extracted from FT and WT. The geochemical distribution maps obtained from FD and SD have been depicted. Information obtained from the exploration drillings such as trenches and boreholes in the study area confirm the analysis results of FT and WT.