Author : Michael Spleit
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (99 download)
Book Synopsis Stochastic Long-term Production Scheduling of the LabMag Iron Ore Deposit in Labrador, Canada by : Michael Spleit
Download or read book Stochastic Long-term Production Scheduling of the LabMag Iron Ore Deposit in Labrador, Canada written by Michael Spleit and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "In long-term production scheduling, which is of vital importance to a project's success and profitability, the goal is to determine a feasible extraction sequence that maximizes the discounted cash flows of a mine while also ensuring the target ore quantities and qualities are met. There is risk of the actual production deviating from what is planned due to geological variability, which is not considered by conventional mine designs and production schedules that are based on a single estimated ore body model. In order to address this issue, multiple simulations of an orebody can be created to represent its geological variability and allow for quantifying expected bounds, instead of single estimates, for grades, tonnages, and financial results. Beyond simply quantifying the geological uncertainty, a mine production schedule can be optimized while directly considering simulations in order to manage the geological risk.In this study, a set of geological simulations of the LabMag iron ore deposit in Labrador, Canada is generated in order to quantify the geological variability in an existing mining schedule and assess the schedule's performance. The 'DBMAFSIM' algorithm is used to provide joint geostatistical simulation of spatially correlated variables of interest. First, a novel application of the method is used to jointly simulate the thicknesses of seven lithological layers, and then four correlated grades within each lithology are jointly simulated. The variability in an existing production schedule, designed based on a single deterministic geological model, is then evaluated using the simulations. This evaluation quantifies the potential deviations from expected production target grades and tonnages as well as the associated financial impact of these deviations. Subsequently, a production schedule optimization based on stochastic integer programming (SIP) is presented that aims to improve mine profitability while simultaneously managing the risk of production tonnage and quality deviations. In addition, the formulation has components for equipment and waste material management: the truck fleet requirements are minimized while ensuring that the number of required trucks is an increasing function to avoid unnecessary peaks; and the evolution of the pit is controlled so that space within the mined out pit is continuously provided to allow for tailings and waste rock to be replaced, thus minimizing the project's environmental footprint." --