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Permanent link (DOI): https://doi.org/10.7939/R35717W74

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Theses and Dissertations

Prediction of Local Uncertainty for Resource Evaluation Open Access

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Other title
Subject/Keyword
geostatistics, localization, mining, uncertainty, resource evaluation, volume variance correction, local uncertainty
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Daniels, Eric B.
Supervisor and department
Clayton Deutsch (Mining Engineering-Geostatistics)
Examining committee member and department
Dr. Hooman Askari-Nasab (Mining Engineering)
Dr. Jeff Boisvert (Mining Engineering - Geostatistics)
Department
Department of Civil and Environmental Engineering
Specialization
Mining Engineering
Date accepted
2015-01-28T13:31:16Z
Graduation date
2015-06
Degree
Master of Science
Degree level
Master's
Abstract
Resource evaluation of a mineral deposit is an important and challenging task. Traditional estimation methods provide a best estimate at the block scale based on available data. The pitfalls of histogram smoothing and conditional bias associated with these methods are well known. Quantifying local uncertainty is an alternative to estimation that avoids these issues. Multiple methods have been established for quantifying local uncertainty and are presented here. This thesis explores the local dependence of change of support methods as well as improves upon available post processing techniques associated with quantifying uncertainty for resource evaluation. Change of support parameters are examined through a simulation test. The advertised benefits and issues surrounding localization of uncertainty are evaluated and a flexible methodology for localization is demonstrated. Artifact reduction techniques are provided for improved localization when a single model is required. Lastly, a case study demonstrates practical implementation of geostatistical methods and post-processing for modeling block scale uncertainty and resource evaluation.
Language
English
DOI
doi:10.7939/R35717W74
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.
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