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Probabilistic Domaining of Aluminum Areas in Iron Deposits

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dc.contributor.author Battalgazy, Nurassyl
dc.contributor.author Madani, Nasser
dc.date.accessioned 2019-08-20T06:38:55Z
dc.date.available 2019-08-20T06:38:55Z
dc.date.issued 2018
dc.identifier.citation Nurassyl Battalgazy and Nasser Madani (2018) Probabilistic Domaining of Aluminum Areas in Iron Deposits. 25th World Mining Congress 2018. Proceedings. Geological Exploration: 17-26 en_US
dc.identifier.uri http://nur.nu.edu.kz/handle/123456789/4140
dc.description.abstract Geostatistical modeling of Iron grade (Fe) in metalliferous deposits is a rationale stage in further analysis of mine design such as mine planning and mineral processing plant optimization. This procedure is becoming important in the case when Fe is controlled by a co-variable that impacts negatively or positively the mechanical characteristics of the steel production. For instance, AL2O3 in most of the iron deposits in a certain level of concentration is helpful to increase the mechanical properties of the steel and in some other level plays as a gangue material which leads to prolonging the mineral processing procedure. Therefore, its 3D modeling is as significant as spatial modeling of Iron, in which it can give the idea of spatial distribution for aluminous areas in a mineral deposit. Geostatistical simulation is a powerful tool that able the practitioners to come up with the uncertainty quantification and consequently the probabilistic description of those areas. ... en_US
dc.language.iso en en_US
dc.publisher 25th World Mining Congress 2018. Proceedings. Geological Exploration. en_US
dc.rights Attribution-NonCommercial-ShareAlike 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/us/ *
dc.subject Iron deposits en_US
dc.subject Aluminum en_US
dc.subject geostatistical modeling en_US
dc.subject co-simulation en_US
dc.subject Turning Band simulation en_US
dc.title Probabilistic Domaining of Aluminum Areas in Iron Deposits en_US
dc.type Article en_US
workflow.import.source science


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