Identifying Mineral Exploration Areas

Identifying Mineral Exploration Areas

A Method for the Selection of Exploration Areas for Unconformity Uranium Deposits by DeVerle P. Harris, Gerard Zaluski, and James Marlatt (Natural Resources Research, 2009)

GeoTotal Group mineral exploration management consultants can help you to develop efficient and effective mineral exploration programs. We can help you evaluate the investment worth of your project portfolio to increase exploration discovery success rates.

Here is an abstract of a technical paper by Deverle Harris, Gerard Zaluski and Jim Marlatt that was published in Natural Resources Research. The paper describes a mathematical geology model for the identification of uranium exploration areas using a Investment Worth System (IWS) and expert judgement. The system model approach can be applied to the exploration for any commodity.

Investment worth model for unconformity related uranium deposits


The method we propose employs two analyses: (1) exploration simulation and risk valuation and (2) portfolio optimization. The first analysis, implemented by the investment worth system (IWS), uses Monte Carlo simulation to integrate a wide spectrum of uncertain and varied components to a relative frequency histogram for net present value of the exploration investment, which is converted to a risk-adjusted value (RAV). Iterative rerunning of the IWS enables the mapping of the relationship of RAV to magnitude of exploration expenditure, X. The second major analysis uses RAV vs. X maps to identify that subset (portfolio) of areas that maximizes the RAV of the firms multiyear exploration budget.

The IWS, which is demonstrated numerically, consists of six components based on the geologic description of a hypothetical basin and project area (PA) and a mix of hypothetical and actual conditions of an unidentified area. The geology is quantified and processed by Bayesian belief networks to produce the geology-based inputs required by the IWS.

An exploration investment of $60 M produced a highly skewed distribution of net present value (NPV), having mean and median values of $4,160 M and $139 M, respectively. For hypothetical mining firm Minex, the RAV of the exploration investment of $60 M is only $110.7 M. An RAV that is less than 3% of mean NPV reflects the aversion by Minex to risk as well as the magnitude of risk implicit to the highly skewed NPV distribution and the probability of 0.45 for capital loss.

Potential benefits of initiating exploration of a portfolio of areas, as contrasted with one area, include increased marginal productivity of exploration as well as reduced probability for nondiscovery. For an exogenously determined multiyear exploration budget, a conceptual framework for portfolio optimization is developed based on marginal RAV exploration products for candidate PAs.

PORTFOLIO, a software developed to implement optimization, allocates exploration to PAs so that the RAV of the exploration budget is maximized. Moreover, PORTFOLIO provides a means to examine the impact of magnitude of budget on the composition of the exploration portfolio and the optimum allocation of exploration to PAs that comprise the portfolio. Using fictitious data for five PAs, a numerical demonstration is provided of the use of PORTFOLIO to identify those PAs that comprise the optimum exploration portfolio and to optimally allocate the multiyear budget across portfolio PAs.

KEY WORDS: Unconformity uranium environments, Bayesian belief network, analog areas, modelling, U3O8 discoveries, stochastic price process, risk-adjusted value, portfolio of exploration areas, optimum allocation of exploration.

Access the paper about identifying uranium exploration areas: Uranium Deposit Exploration Model

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