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Mineral Resources Evaluation with Mining Selectivity and Information Effect
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- Author / Creator
- Chiquini, Ana P
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Long term mineral resources modeling is done to predict tonnage and grade of ore that may be mined and represents a key feature in the development of any mining project. The most common approach used in the mining industry is to estimate the grades using ordinary kriging and report the recoverable resources based on this deterministic estimated model. Mineral resources calculated with kriging are a smooth representation of the actual distribution of grades and they do not provide an assessment of uncertainty. Other approaches include probabilistic estimation and geostatistical simulation, that provide an assessment of uncertainty. Unlike kriging, simulation reproduces the variability of the mineral deposit. Reporting mineral resources directly on high resolution simulation results would assume perfect knowledge of the grade at the time of mining and selectivity at the scale of the data, without considering mining practice constraints. There will always be uncertainty left at the time of mining because even the grade control sampling is imperfect, so assuming perfect knowledge of the grade in the future is not correct. In addition, mineral resources are evaluated at a specific time considering only the information available at that time. There are two concerns when geostatistical simulation is used for resources modeling: the information and the mining selectivity effects. The information effect is the decrease in uncertainty from the resources model to the time of mining, as more or better information becomes available. The mining selectivity effect is the selectivity or scale that would match future mining practice and geological constraints. The determination of ore (and mineable dig limits) must consider mining selectivity and the information available at the time of mining. A new framework for resource calculations is proposed with two separate modules to address those concerns. The information effect is accounted for by anticipating the additional production data that will be available at the time mining to guide the destination for the mined material. The mining selectivity effect is addressed by mimicking the grade control procedure to get mineable dig limits at a chosen selectivity, represented by a minimum mineable unit size. The proposed methodology is mainly designed for open pit mining. An adaptation to underground mining, more specifically to sublevel stoping of a tabular vein deposit, is also developed. In addition to a prediction of recoverable resources that will be closer to the material mined in the future, the framework proposed provides an assessment of local and global uncertainty for risk management.
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- Graduation date
- Fall 2018
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- Type of Item
- Thesis
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- Degree
- Master of Science
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- License
- 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.