Block-Cave Extraction Level and Production Scheduling Optimization under Grade Uncertainty

  • Author / Creator
    Saha, Malaki
  • Nowadays, application of massive mining methods has been increased due to the economic condition of mining companies. It is a step change for the industry, from the traditional open-pit to a move underground. Among the underground mining methods available, caving methods are favored because of their low-cost and high-production rates. They offer a much smaller environmental footprint compared to equivalent open-pit operations due to the much smaller volume of waste to be moved and handled. Planning of caving operations poses complexities in different areas such as safety, environment, ground control, and production scheduling. As the mining industry is faced with more marginal resources, it is becoming essential to generate production schedules that will provide optimal operating strategies while meeting practical, technical, and environmental constraints. Unfortunately, common methodologies and tools used in mining industry for block-cave scheduling are not adequate in dealing with the complexity of the optimal production scheduling of mineable deposits. Also, the traditional long-term mine planning is based on deterministic ore-body models, which ignore the uncertainty in the geological resources. Grade uncertainty has profound impact on production targets which also impacts the financial expectations of the project. Initial evaluation of a range of levels for starting the extraction of block-cave mining is an important issue that needs to consider a variety of parameters including extraction rate, block height, discount rate, block profit, cost of mining and processing and revenue factors. The objective of this study is to present a methodology to find the best extraction level and the optimum sequence of extraction for that level under grade uncertainty. A set of simulated realizations of the mineral grade is modeled based on stochastic sequential simulation to address this problem. The average grade of all the realizations is calculated and a new block model is generated, called average-simulated block model (first case study). Another case study is original block model which is created from the drillhole data. A method is introduced to find the best level to start extraction based on the maximum discounted ore profit. The best level of extraction is determined for all the realizations, original and average-simulated block models. Then, Maximum net present value (NPV) is obtained using a mixed-integer linear programming (MILP) model given some constraints such as mining capacity, production grade, extraction rate and precedence. Application of the method has been verified on both original and average-simulated block models for block cave production scheduling over 15 Periods. The best level for the original bock model was 38 and for average-simulated block model was 39. The obtained NPVs were $0.925B and $0.726B for the original and average-simulated block models, respectively, and all the constraints were satisfied. Finally, risks associated with grade uncertainty are investigated and analyzed which considerably helps the decision makers in better understanding of various cases and conditions. Among all the examined scenarios with unique scheduling parameters, the worst and the best case for the NPV were $0.85B and $1.081B, respectively. The ore tonnage also varies between 28.68Mt and 39.64Mt.

  • Subjects / Keywords
  • Graduation date
    2016-06:Fall 2016
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
  • Institution
    University of Alberta
  • Degree level
  • Department
    • Department of Civil and Environmental Engineering
  • Specialization
    • Mining Engineering
  • Supervisor / co-supervisor and their department(s)
    • Pourrahimian, Yashar (Civil and Environmental Engineering)
  • Examining committee members and their departments
    • Hall, Robert (Civil and Environmental Engineering)
    • Liu, Wei Victor (Civil and Environmental Engineering)