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

TALANTA

卷:85

Article

Figueroa-Cisterna, J.²  Bagur-Gonzalez, M. G.^1,3  Morales-Ruano, S.^2,3  Carrillo-Rosua, J.^3,4  Martin-Peinado, F.⁵ 

[1] Univ Granada, Dept Analyt Chem, Fac Sci, E-18071 Granada, Spain

[2] Univ Granada, Dept Mineral & Petrol, Fac Sci, E-18071 Granada, Spain

[3] Univ Granada, Fac Sci, Inst Andaluz Ciencias Tierra, CSIC, E-18071 Granada, Spain

[4] Univ Granada, Fac Educ Sci, Dept Didact Expt Sci, E-18071 Granada, Spain

[5] Univ Granada, Dept Soil Sci, Fac Sci, E-18071 Granada, Spain

关键词: Portable X ray fluorescence analyser (P-XRF);    Box-Cox transformation;    Pattern recognition techniques;    Ore exploration;    Cu-(Ag) deposits;   

DOI  :  10.1016/j.talanta.2011.07.034

来源: Elsevier

【 摘 要 】

The combination of ex situ portable X ray fluorescence with unsupervised and supervised pattern recognition techniques such as hierarchical cluster analysis, principal components analysis, factor analysis and linear discriminant analysis have been applied to rock samples, in order to validate a in situ macroscopic 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 analysed elements were Ca, Cu, Fe, K. Mn, Pb, Rb, Sr, Ti and Zn. The statistical treatment of the geological data has been arisen from the application of the Box-Cox transformation used to transform the data set in normal form to minimize the non-normal distribution of the data. From the statistical results obtained it can be concluded that the macroscopic classification applied to the transformed data permits at least, to distinguish 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). (C) 2011 Elsevier B.V. All rights reserved.

【 授权许可】

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