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Permanent link (DOI): https://doi.org/10.7939/R34J0B55D

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Spatial Modelling of Heavy-Tailed Mineral Grades Using a Spatial Point Process Open Access

Descriptions

Other title
Subject/Keyword
resource estimation
geostatistics
spatial point process
discrete fracture network
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Mooney, Cole R
Supervisor and department
Boisvert, Jeff B (Mining Engineering)
Examining committee member and department
Szymanski, Jozef (Mining Engineering)
Askari-Nasab, Hooman (Mining Engineering)
Liu, Victor Wei (Mining Engineering)
Department
Department of Civil and Environmental Engineering
Specialization
Mining Engineering
Date accepted
2015-03-31T09:07:13Z
Graduation date
2015-06
Degree
Master of Science
Degree level
Master's
Abstract
Evaluating the resource contained in a precious metals deposit is a challenging task because they are often characterized by heavily-skewed grade distributions and outlier values. Traditional geostatistical modelling methods are difficult to apply in the presence of outlier values because they can lead to overestimation and bias. The economic viability of these deposits often depends on the upper few percent of samples. These outlier samples are important and should be retained; however, their influence should be reduced to prevent potential overestimation and bias. This thesis examines the implications of modelling heavy-tailed, precious metals deposits. The limitations of traditional geostatistical modelling techniques are discussed in the context of heavy-tailed deposits and the use of a spatial point process to model grade is presented. An overview of the geologic processes that create gold deposits is presented in order to understand the nature of gold mineralization as well as provide justification for the proposed modelling technique. A spatial point process is used to model the tail of the distribution as discrete events. A particle size distribution is given to the simulated points to calculate grade. Following that, a discrete fracture network is adapted to model mineralized quartz veins in the deposit. High-grade gold is spatially restricted to the simulated vein structures. The automatic processing of drill core photos generates the necessary input distributions for a fracture network. Finally, a thorough case study demonstrates the application of grade modelling with a spatial point process and discrete fracture network. The results are compared to traditional geostatistical techniques and limitations are discussed. The proposed methodology presents a geologically realistic method of simulation which reduces the effect of outlier values by spatially limiting their influence. Capping or other subjective ad-hoc manipulation of assay data is not required. Final models of grade have the correct mean, variance and spatial continuity.
Language
English
DOI
doi:10.7939/R34J0B55D
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
Mooney, C.M., Board, W. & Boisvert, J.B. (2015). Modelling heavy-tailed coarse gold deposits with a spatial point process. The Journal of the Canadian Institute of Mining and Metallurgy, In Press.

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