Using large support data to improve grade prediction in underground mining

Marcel Antonio Arcari Bassani, Péricles Lopes Machadob, João Felipe Coimbra Leite Costa, Ricardo Hundeishaussen Rubio

Producción científica: Capítulo del libro/informe/acta de congresoPonencia publicada en las memorias del evento con ISBNrevisión exhaustiva

Resumen

In underground mining, grade data are informed at different support volumes. Drillhole data are defined at a quasi-point support while production data represent tons of ore mined during a period of time (stopes). From a geostatistical point of view, both data should be used to build a geostatistical model. However, the support difference must be considered. In this study, the block kriging approach is proposed to combine these two types of data. A synthetic underground mining case is presented. Two estimation scenarios were evaluated. The first considers only drillhole data while the second considers both drillhole and production data. Results showed that the use of production data improved grade estimation.

Idioma originalInglés
Título de la publicación alojadaApplication of Computers and Operations Research in the Mineral Industry - Proceedings of the 37th International Symposium, APCOM 2015
EditoresSukumar Bandopadhyay, Snehamoy Chatterjee, Tathagata Ghosh, Kumar Vaibhav Raj
EditorialSociety for Mining, Metallurgy and Exploration (SME)
Páginas85-91
Número de páginas7
ISBN (versión digital)9780873354172
EstadoPublicada - 2015
Publicado de forma externa
Evento37th International Symposium on Application of Computers and Operations Research in the Mineral Industry, APCOM 2015 - Fairbanks, Estados Unidos
Duración: 23 may. 201527 may. 2015

Serie de la publicación

NombreApplication of Computers and Operations Research in the Mineral Industry - Proceedings of the 37th International Symposium, APCOM 2015

Conferencia

Conferencia37th International Symposium on Application of Computers and Operations Research in the Mineral Industry, APCOM 2015
País/TerritorioEstados Unidos
CiudadFairbanks
Período23/05/1527/05/15

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