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Date of Award
2017
Document Type
Campus Access Master's Thesis
Degree Name
Master of Science in Mining Engineering (MS)
Administrative Home Department
Department of Geological and Mining Engineering and Sciences
Advisor 1
Snehamoy Chatterjee
Committee Member 1
Thomas Oommen
Committee Member 2
Ebrahim Karimi Tarshizi
Abstract
Mineral deposits are the main assets for the mining industry. Mineral deposits are estimated based on the findings of exploration drilling. Complex host geology with variable grades and geological controls increases difficulty in resource estimation. In these situations, volume (tonnage) and grade are often over- or underestimated, resulting in inaccurate mine plan that leads to costly financial decisions. In this study, a multiple-point geostatistical method, namely Single Normal Equation Simulation (SNESIM) was applied to generate equiprobable orebody models for a copper deposit from Africa that helps to analyze the uncertainty of ore tonnage of the deposit. The grade uncertainty was evaluated by generating multiple realization of grade models using sequential Gaussian simulation within each equiprobable orebody models. The results are validated by generating the marginal distribution, and two- and three-point statistics. In addition, a comparative study is performed for the deterministic version, the stochastic version with grade uncertainty, and the stochastic version with volume and grade uncertainty. The results show that the orebody model with the maximum volume is 4.8% more than the average volume and the minimum volume is 5.1% less than the average volume. The grade simulation results demonstrate that the average grade for all simulations is 3.89%, but average grade for different simulations varied from 3.6% to 4.1%. The results also show that the volume and grade uncertainty model overestimated the orebody volume compared to the conventional orebody volume. The long-term production schedule is generated taking into account the volume and grade uncertainties from the orebody models, and satisfying mine production capacity and xi processing capacity constraints. The production schedule results for the volume and grade uncertainty-based model are compared to the production schedule generated from deterministic orebody model, and grade uncertainty-based model. The results demonstrated that the incorporation of both the volume and grade uncertainty significantly reduces the risk of deviation from the target. The results also show that incorporation of volume and grade uncertainty increases the net present value (NPV) of mining project, when compared to the mine plan generated from the deterministic model and stochastic model with only grade uncertainty. The results show that the production schedule generates high revenue over wide range of initial assumptions and the expected NPV is 3% higher than the deterministic version. A sensitivity analysis was also performed to understand the effect of penalty factor for deviating the constraints.
Recommended Citation
Paithankar, Amol, "RISK CONTROL IN PRODUCTION SCHEDULING BY CONSIDERING VOLUME AND GRADE UNCERTAINTIES IN RESOURCE ESTIMATION", Campus Access Master's Thesis, Michigan Technological University, 2017.