Scholarly record

APPLYING DISCRIMINANT ANALYSIS AND SGS TO SEPARATING ALTERATION ZONES WITHIN THE SUNGUN PORPHYRY COPPER DEPOSIT

O. Asghari, A. Hezarkhani, V. Rafiee

Abstract

In the detailed exploration and reserve estimation, with separating the alteration (as the controller of the grade) in ore reserve and estimating the reserve in each alteration, the estimation variance will decrease and the accuracy of the estimation will increase. This paper tries to quantify and separate the alterations using discriminant analysis, a multivariate statistical method, and distribute them through sequential gaussian simulation in the Sungun copper deposit. A simple linear discriminant function transforms an original set of measurements on a specimen into a single discriminant score (Ri). Parameters include four measurements: homogenization temperature, salinity and density of hydrothermal fluid and pressure which could be obtained from the fluid inclusion study and other auxiliary parameters: containing copper and elevation level of each sample. Discriminant score ranges from -3 to 7 and is interpreted as a regional variable. To carry out a geostatistical investigation, a spherical model was fitted over an empirical variogram of Ri. For simulating the Ri via Sequential Gaussian Simulation (SGS) method, data were transferred to standard normal and then simulated one hundred times. All of the realizations were honor to histogram and variogram, so all realizations are valid. After this process, all blocks of the block model which was made for copper estimation were simulated. Based on the simulated scores and R0 (a critical score for separating two alterations), all blocks were categorized into two alterations: phyllic and potassic. This method can determine the alteration type and can also determine the intensity of the alteration in the porphyry copper deposits. On the other hand the sequential indicator simulations based on 17089 alteration type analyses (10210 analyses for phyllic alteration and other for potassic) was applied to the deposit and categorized potassic and phyllic alterations. The results of the alteration quantifying in comparison with the results of simulation of indicated alterations showed high-conformity.

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