The use of a combined portable X ray fluorescence and multivariate statistical methods to assess a validated macroscopic rock samples classification in an ore exploration survey

Abstract

The combination of “ex situ” portable X ray fluorescence with unsupervised and supervised pattern recog-nition techniques such as hierarchical cluster analysis, principal components analysis, factor analysis andlinear discriminant analysis have been applied to rock samples, in order to validate a “in situ” macro-scopic rock samples classification of samples collected in the Boris Angelo mining area (Central Chile),during a drill-hole survey carried out to evaluate the economic potential of this Cu deposit. The analysedelements were Ca, Cu, Fe, K, Mn, Pb, Rb, Sr, Ti and Zn. The statistical treatment of the geological datahas been arisen from the application of the Box–Cox transformation used to transform the data set innormal form to minimize the non-normal distribution of the data. From the statistical results obtained itcan be concluded that the macroscopic classification applied to the transformed data permits at least, todistinguish quite well in relation to two of the rock classes defined (70.5% correctly classified (p < 0.05))as well as for four of the five alteration types defined “in situ” (75% of the total samples).