Incorporating geological and market uncertainties and operational flexibility into open pit mine design

This work outlines a procedure for integrating uncertainty and operational flexibility into open pit mine design selection. A multi-criteria design ranking system based on advanced uncertainty and financial modeling techniques such as Monte Carlo simulation and real options is proposed. A case study at a copper mine is provided.

[1]  Roussos Dimitrakopoulos,et al.  Stochastic optimisation model for open pit mine planning: application and risk analysis at copper deposit , 2007 .

[2]  Eduardo S. Schwartz The stochastic behavior of commodity prices: Implications for valuation and hedging , 1997 .

[3]  Roussos Dimitrakopoulos,et al.  Moving forward from traditional optimization: grade uncertainty and risk effects in open-pit design , 2002 .

[4]  Mohammad Waqar Ali Asad,et al.  Multi-period quarry production planning through sequencing techniques and sequencing algorithm , 2008 .

[5]  S. A. Abdel Sabour,et al.  Valuing Real Capital Investments Using The Least-Squares Monte Carlo Method , 2006 .

[6]  M. Kumral,et al.  Mine design selection under uncertainty , 2008 .

[7]  R. Dimitrakopoulos,et al.  A maximum upside / minimum downside approach to the traditional optimization of open pit mine design , 2007 .

[8]  G. Davis,et al.  Valuing uncertain asset cash flows when there are no options: A real options approach , 2005 .

[9]  J. Whittle,et al.  A decade of open pit mine planning and optimization - The craft of turning algorithms into packages , 1999 .

[10]  Mark Zuckerberg,et al.  Optimal life-of-mine scheduling for a Bauxite mine , 2011 .

[11]  M. Vallee,et al.  Mineral resource + engineering, economic and legal feasibility = ore reserve , 2000 .

[12]  Jef Caers,et al.  Representing Spatial Uncertainty Using Distances and Kernels , 2009 .

[13]  R. Dimitrakopoulos,et al.  Stochastic integer programming for optimising long term production schedules of open pit mines: methods, application and value of stochastic solutions , 2008 .

[14]  Roussos Dimitrakopoulos,et al.  Stope design and geological uncertainty: Quantification of risk in conventional designs and a probabilistic alternative , 2009 .

[15]  Alexandre Boucher,et al.  Block Simulation of Multiple Correlated Variables , 2009 .

[16]  M. Slade Valuing Managerial Flexibility: An Application of Real-Option Theory to Mining Investments , 2001 .

[17]  Francis A. Longstaff,et al.  Valuing American Options by Simulation: A Simple Least-Squares Approach , 2001 .

[18]  Chan S. Park,et al.  Decision Making Under Uncertainty—Real Options to the Rescue? , 2002 .

[19]  Peter Tufano,et al.  When are Real Options Exercised? An Empirical Study of Mine Closings , 2000 .

[20]  Salih Ramazan,et al.  The new Fundamental Tree Algorithm for production scheduling of open pit mines , 2007, Eur. J. Oper. Res..

[21]  Roussos Dimitrakopoulos,et al.  A risk quantification framework for strategic mine planning: Method and application , 2011 .

[22]  Roussos Dimitrakopoulos,et al.  Evaluating mine plans under uncertainty: Can the real options make a difference? , 2007 .