Managing Mining Risk Using Ore Reserve Estimates

dc.contributor.authorOdertey, Felix
dc.date.accessioned2012-11-15T12:24:09Z
dc.date.accessioned2023-04-19T15:34:55Z
dc.date.available2012-11-15T12:24:09Z
dc.date.available2023-04-19T15:34:55Z
dc.date.issued2012
dc.descriptionA Thesis submitted to the Institute of Distance Learning, Kwame Nkrumah University of Science and Technology, Kumasi in partial fulfillment of the requirements for the degree of Master of Science in Industrial Mathematicsen_US
dc.description.abstractThe decision to invest in the mining industry comes with all forms of challenges that will have to be managed with care. Especially because, it involves huge capital outlay and the associated risks are very high. The assessment process of the commercial viability of the ore deposit consists of two major components; the estimation of the quantity (including quality) of the commodity and the decision as to whether or not to mine (or invest). This thesis tries to explore these risk areas by using the geostatistical model and its analysis (the semi-variogram and kriging analysis) to estimate the quantity and quality of the commodity. The decision to invest or not to invest is analyzed with the help of the black-scholes model, taking into consideration the prevailing market price (including price volatility) and the risk derived from the geostatistical estimates. The results indicate that, if the concession is contracted for a period of five years then the mine would be viable for investment during the entire duration when the price, the base case, of the commodity (gold) is about one thousand six hundred dollars. The sensitivity analysis, however, reveals that the mine would not be worth investing within some periods in the duration of the contract especially when the gold price falls to eight hundred dollars per ounce and below.  en_US
dc.description.sponsorshipKNUSTen_US
dc.identifier.urihttps://ir.knust.edu.gh/handle/123456789/4550
dc.language.isoenen_US
dc.titleManaging Mining Risk Using Ore Reserve Estimatesen_US
dc.typeThesisen_US
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