Framework for resource uncertainty prediction and data valuation: An application to diamond deposits

CIM Journal, Vol. 6, No. 3, 2015, pages 178-190

J. G. Manchuk
Centre for Computational Geostatistics, University of Alberta, Edmonton, Alberta, Canada

J. Stiefenhofer and M. Thurston
Global Mining Division, De Beers Group Services (Pty) Limited, Southdale, South Africa

C. V. Deutsch
Centre for Computational Geostatistics, University of Alberta, Edmonton, Alberta, Canada

http://dx.doi.org/10.15834/cimj.2015.19
Résumé Il est important de quantifier le degré d’incertitude associé à une ressource diamantifère naturelle, depuis le moment de sa découverte et durant toute la durée de l’exploitation. La collecte de données se fait durant les phases de découverte, d’exploration, de délimitation, et de production ou de récupération. La quantification de la relation entre les données et l’incertitude est une composante importante de l’évaluation du projet. La valeur des données est mesurée en tant que leur potentiel à réduire l’incertitude si elles sont recueillies. Une méthode a été développée qui utilise la simulation de Monte Carlo pour prédire l’incertitude de la ressource et évaluer les données durant les phases critiques du développement, surtout celles de la découverte et de l’exploration. La technique est appliquée à des gisements de cheminées diamantifères.
Mots-Clé Exploration pour des diamants, géostatistique, incertitude de la ressource, kimberlite, simulation de Monte Carlo
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