MINERAL RESOURCE MODELING OF VARIABLES WITH INEQUALITY CONSTRAINTS: A CASE STUDY OF AN IRON ORE DEPOSIT

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Date

2021-09

Authors

Abulkhair, Sultan
Madani, Nasser

Journal Title

Journal ISSN

Volume Title

Publisher

APCOM 2021

Abstract

In multivariate geostatistics, it is common to have different types of complexities between variables of interest. In this context, an inequality constraint is an example of complex bivariate relationships. Unfortunately, traditional co-kriging and co-simulation algorithms cannot reproduce this type of bivariate complexity, leading to the overestimation of disturbing elements. This paper proposes a new algorithm based on a hierarchical sequential Gaussian co-simulation framework, integrated with inverse transform sampling, to model inequality constraints between variables. First, the proposed methodology's validity was evaluated by applying it to a real case study from an iron deposit, with an inequality constraint between iron and aluminum oxide. Then the simulated results were compared with a conventional hierarchical co-simulation algorithm to investigate the effect of inverse transform sampling on the quality of the co-simulation. The results showed that the proposed algorithm can reproduce an inequality constraint between variables.

Description

Keywords

Geostatistics, Mineral resource, Inequality constraint

Citation

Abulkhair, S., Madani, N. (2021). Mineral resource modeling of variables with inequality constraints: A case study of an iron ore deposit. In the proceeding of the APCOM 2021. Musingwini, C. Woodhall, M (eds.), Johannesburg, South Africa, p. 449-458.