Abstarct: Mineral resource exploration has always been the focus of interest in the field of geoscience and thereby, various techniques have been developed for this purpose. The aim of this research work is to investigate whether the spectral induced polarization (SIP) data modeling and recovering the induced polarization effects from 1-D inversion of frequency domain helicopter-borne electromagnetic data (HEM-IP) is possible for the purpose of polarizable resource exploration. Furthermore, the analyses of geological, litho-geochemical and mineralogical data and ground-baxsed geophysical induced polarization and resistivity (IP-Res.) surveys have been conducted for validating the result of both the SIP and HEM-IP modeling. We conducted our case study in the Kervian area located in the southwest of Saqqez city, northwest of Sanandaj-Sirjan zone. In the study area, gold mineralization is associated with quartz and pyrite minerals. However, two varieties of pyrite mineral including coarse-grained barren and fine-grained auriferous mineral have occurred in the study area. The occurrence of sulfide mineral, i.e. pyrite mineral, as well as the difference between the sizes of pyrite minerals is a favorite target for SIP investigation. Therefore, in the first step of this research work, we acquired the SIP data from 33 pieces taken from the core samples of the mineralized zone of Kervian gold deposit. To model the acquired SIP data, we applied different relaxation models including the Cole-Cole, double-phase generalized Cole-Cole, Deby decomposition and spherical and ellipsoidal GEMTIP. To recover the relaxation model parameters, we implemented a least square and combined genetic algorithm and particle swarm optimization (CGAPSO) algorithm. The results of our research revealed that all of the relaxation models are well fitted to the complex resistivity/conductivity spectra. However, the recovered model parameters of single phase Cole-Cole and the double-phase generalized Cole-Cole provide the most reliable information considering the results of mineralogical evidences. Moreover, the failure of spherical GEMTIP to recover the reliable model parameter from the measured SIP data has been revealed. In addition, the ellipsoidal GEMTIP modeling of noisy synthetic data indicates that recovering of either time constant or ellipticity cannot be achieved well because of the mutual interaction between these relaxation model parameters. However, as a prominent result of this part of our research, we could to discriminate two varieties of pyrite mineral using SIP data modeling, successfully. The result of our investigation is also verified using mineral liberation analysis (MLA) data analysis. Our investigation, also, revealed that incorporating the SIP data into the HEM data shifts the magnitude of real part of acquired HEM data in the low frequency and it may get negative value if the IP effect is strong. This feature could be used as a novel signature for detecting the polarizable formations using frequency-domain electromagnetic data. Thereby, we developed a hybrid algorithm baxsed on very fast simulated annealing and Marquardt-Levenberg (VFSA-ML) methods for recovering the corresponding model parameters from 1-D inversion of HEM data. We applied the code to recover the Cole-Cole model parameters from the HEM data acquired from Kervian gold deposit successfully. Furthermore, we implemented the imperialist competitive (ICA) algorithm to recover the SIP model parameters from synthetic HEM data successfully. Then, we applied a multivariate statistical robust principal component analysis (PCA) to extract the multivariate structure of both compositional and log-ratio transformed litho-geochemical data of Kervian gold deposit. Robust PCA of untransformed data is not capable of certifying element association. However, in the robust PCA analysis of transformed data, both varieties of gold mineralization have been revealed. The first gold occurrence is detected in PC1 and it is associated with Pb, As, Hg, Mo, S and Sb elements in quartz-sulfide veins. The second one, PC4, could be correlated with quartz veins. The results indicate that the robust PCA of logratio transformed data improves the interpretation of geochemical data and provides more reliable information about the gold mineralization of the type sought. Eventually, the gold potential mapping has been performed by combining the exploratory evidential maps, i.e., geological, geophysical and geochemical maps, using fuzzy analytic hierarchy process (FAHP) in the geographic information system (GIS) environment. The main anomaly of Kervian area is detected using our approach and it is also validated by ground-baxsed geophysical IP-Res. Surveys.