Chapter (19): Advanced Analytics in Valuation of Mine Prospects and Mining Projects


In an open-pit metalliferous deposit, evaluation of optimal cut-off grade plays a significant role in shaping the project dynamics by determining the project’s profitability during mine planning and designing activity. The nature of the cut-off grade is dynamic, and therefore the application of dynamic programming may be considered one of the suitable methods for its optimization. A computer-driven model, namely the cut-off grade optimizer (COGO) derived from a dynamic programming algorithm built-in Visual Basic using C# programming language, has been developed. The purpose of the optimizer is to find out the optimum cut-off grade, which iterates through the range of grades. Net present value (NPV) maximization is the objective of the algorithm subject to the complex constraints in mining, milling, concentrating, and refining operations. This software tool has three sections: the Data Input section, the Data Output section, and the Graphical Result section. The algorithm and the associated software have been validated using a portion of the data of Sarcheshmeh copper mine from a published paper. The results of the analysis are encouraging. The optimum cut-off grade of the copper deposit has been determined to be 0.24% resulting in a maximum NPV of ₹ 83,714 million, with an optimized mine life of 23.5 years, and the average mill head grade corresponds to 0.707%. All details of the developed application are presented in this chapter as a case study of using advanced data analytics for the Evaluation of Optimum Cut-Off Grade.

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Chapter Includes

  • 6 Parts
  • 2 Forms