عنوان مقاله [English]
In order to achieve maximum information hidden in raw geophysical data and to enableing accurate interpretation consistent with geological data, geophysical inverse modeling has been devised and routinely employed by explorationists. However in some cases due to both complex nature of most earththe earth systems and influence of some parameters unrelated to the sought mineralization, this methodology has resulted in unsatisfactory results. A crucial case is encountered in the joint interpretation of Resistivity and Induced Polarization (RS/IP) datasets. Usually combined RS/IP method plays important role in most porphyry copper exploration programs. However drillings has revealed that high IPs corresponds to high pyritic zones with low copper content therefore misleading the exploration program. In the present study RS/IP data are were integrated with the corresponding lithology, alteration and assay data from drilling dataand followed by applying discriminant function analysis was applied to separate high from low grade copper zones at Chahfirouzeh porphyry copper deposit, Iran. Through employing lithological and alteration data, the performance of discriminant function analysis has been improved considerably compared to the case where only IP and RS data were used. The final model has yielded a linear statistical model by which high copper grade zone can be discriminated from zones with high IP and low Cu contents. Validation through the drillings has confirmed that 90% and 87% correct classification is achieved for discriminating high and low grade ore zones respectively.