Geometallurgical estimation of the work index based on synthetic domains

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The multidisciplinary geometallurgical modeling of the value chain is dependent on the areas of geology, mining and metallurgy, for this reason it is of the utmost importance in estimating the resources of the deposit. The objective of this study is to determine a methodology for modeling non-additi...

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Detalles Bibliográficos
Autores: Castro Andrade, Julio Alejandro, Calderón Celis, Julia Marilú
Formato: artículo
Fecha de Publicación:2023
Institución:Universidad Nacional Mayor de San Marcos
Repositorio:Revistas - Universidad Nacional Mayor de San Marcos
Lenguaje:español
OAI Identifier:oai:ojs.csi.unmsm:article/25235
Enlace del recurso:https://revistasinvestigacion.unmsm.edu.pe/index.php/iigeo/article/view/25235
Nivel de acceso:acceso abierto
Materia:Conminución
Work Index
geoquímica
árboles de decisión y geometalurgia
Comminution
work index
geochemistry
decision trees and geometallurgy
Descripción
Sumario:The multidisciplinary geometallurgical modeling of the value chain is dependent on the areas of geology, mining and metallurgy, for this reason it is of the utmost importance in estimating the resources of the deposit. The objective of this study is to determine a methodology for modeling non-additive variables such as the work index. The methodology is based on the fact that there are geometallurgical variables whose average values do not correspond to the arithmetic mean of the domain, this is the case of metallurgical hardness variables. To achieve this objective, the database of a 100 linear km drilling campaign was used for the generation of comminution metallurgical composites, geochemical analysis and geological logging. The synthetic domain modeling was developed based on the redefinition of the alteration geochemical domains through the use of decision trees and the work index metallurgical test. A comparison of the modeling of the work index with classical geostatistics was made with respect to the proposal, finding improvements in the predictability of the R2 values of 74.56% and 93.50%, respectively. The results show that the synthetic modeling methodology based on geochemistry is based on the formation of the gangue and the host rock.
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