Change of support using non-additive variables with Gibbs Sampler: Application to metallurgical recovery of sulphide ores
| Autor: | Roberto Miranda, Julián M. Ortiz, Brian Townley, Mauricio Garrido, Francisco Villaseca, W. Kracht |
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| Rok vydání: | 2019 |
| Předmět: |
Multivariate statistics
Multivariable calculus 0208 environmental biotechnology Change of support Metallurgy 02 engineering and technology 010502 geochemistry & geophysics 01 natural sciences 020801 environmental engineering symbols.namesake Additive function symbols Environmental science Gangue Computers in Earth Sciences Smoothing 0105 earth and related environmental sciences Information Systems Downscaling Gibbs sampling |
| Zdroj: | Computers & Geosciences. 122:68-76 |
| ISSN: | 0098-3004 |
| Popis: | Flotation tests at laboratory scale describe the metallurgical behavior of the minerals that will be processed in the operational plant. This material is generally composed of ore and gangue minerals. These tests are usually scarce, expensive and sampled in large supports. This research proposes a methodology for the geostatistical modelling of metallurgical recovery, covering the change of support problems through additive auxiliary variables. The methodology consists of simulating these auxiliary variables using a Gibbs Sampler in order to infer the behavior of samples with smaller supports. This allows downscaling a large sample measurement into smaller ones, reproducing the variability at different scales considering the physical restrictions of additivity balance of the metallurgical recovery process. As a consequence, it is possible to apply conventional multivariate geostatistical tools to data at different supports, such as multivariable exploratory analysis, calculation of cross-variograms, multivariate estimations, among others. The methodology was tested using a drillhole database from an ore deposit, modelling recovery at a smaller support than that of the metallurgical tests. The support allowed for the use of the geochemical database, to consistently model the metal content in the feed and in the concentrate, in order to obtain a valid recovery model. Results show that downscaling the composite size reduces smoothing in the final model. |
| Databáze: | OpenAIRE |
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