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dc.contributor.authorBarr, Drew
dc.contributor.otherQueen's University (Kingston, Ont.). Theses (Queen's University (Kingston, Ont.))en
dc.date2012-04-29 22:08:19.283en
dc.date2012-04-30 22:36:51.257en
dc.date.accessioned2012-05-01T15:59:23Z
dc.date.available2012-05-01T15:59:23Z
dc.date.issued2012-05-01
dc.identifier.urihttp://hdl.handle.net/1974/7180
dc.descriptionThesis (Master, Mining Engineering) -- Queen's University, 2012-04-30 22:36:51.257en
dc.description.abstractMining operations exploit mineral deposits, processing a portion of the extracted material to produce salable products. The concentration of valuable commodities within these deposits, or the grade, is heterogeneous. Not all material has sufficiently high grades to economically justify processing. Cut-off grade is the lowest grade at which material is considered ore and is processed to create a concentrated commodity product. The choice of cut-off grade at a mining project can be varied over time and dramatically impacts both the operation of the mine and the economics of the project. The majority of literature and the accepted industry practices focus on optimizing cut-off grade under known commodity prices. However, most mining operations sell their products into highly competitive global markets, which exhibit volatile commodity prices. Making planning decisions assuming that a given commodity price prediction is accurate can lead to sub-optimal cut-off grade strategies and inaccurate valuations. Some academic investigations have been conducted to optimize cut-off grade under stochastic or uncertain price conditions. These works made large simplifications in order to facilitate the computation of a solution. These simplifications mean that detailed mine planning data cannot be used and the complexities involved in many real world projects cannot be considered. A new method for optimizing cut-off grade under stochastic or uncertain prices is outlined and demonstrated. The model presented makes use of theory from the field of Real Options and is designed to incorporate real mine planning data. The model introduces two key innovations. The first is the method in which it handles the cut-off grade determination. The second innovation is the use of a stochastic price model of the entire futures curve and not simply a stocastic spot price model. The model is applied to two cases. The first uses public data from a National Instrument 43-101 report. The second case uses highly detailed, confidential data, provided by a mining company from one of their operating mines.en_US
dc.languageenen
dc.language.isoenen_US
dc.relation.ispartofseriesCanadian thesesen
dc.rightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.en
dc.subjectReal Optionsen_US
dc.subjectMine planningen_US
dc.subjectEconomicsen_US
dc.subjectMine designen_US
dc.subjectMine evaluationen_US
dc.subjectCut-offen_US
dc.subjectHedgingen_US
dc.subjectSimulationen_US
dc.subjectFinanceen_US
dc.subjectMine optimizationen_US
dc.subjectValuationen_US
dc.subjectMiningen_US
dc.subjectOptimizationen_US
dc.subjectStochasticen_US
dc.subjectCut-off gradeen_US
dc.titleStochastic Dynamic Optimization of Cut-off Grade in Open Pit Minesen_US
dc.typethesisen_US
dc.description.degreeMasteren
dc.contributor.supervisorMartin, Jimen
dc.contributor.departmentMining Engineeringen


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