When should a producer increase production? The optimal time to increase production is when the mineable resource is large enough to support the operation. Sustaining current levels and maintaining profits over the long term require growing your resource base.
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This is achieved through further development of the deposit and ongoing exploration near the deposit. The life of a mining operation is often partitioned into linear stages, with exploration, development and production being the three major phases. However, to think of each of these activities as separate from and leading into the next does not adequately represent the true nature of a mining operation. Exploration and development do not end once production begins.
Exploration and development activities are essential for growing a mineable resource base and sustaining production to keep the mill running at full capacity, while also extending mine life. Development work allows miners to reach previously inaccessible bodies of ore and convert resources into reserves.
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New advanced exploration technologies and sophisticated analytical techniques are making it possible to refresh the resource base through new discoveries. To build out the resource at a given mine site, producers focus their exploration efforts on three areas: in mine, near mine and regional. In-mine work generally includes development work designed to gain further access to economical orebodies, as well as geological modeling and definition drilling to extend the known mineral resources. Typically only proven and probable reserves, as well as measured and indicated resources, are included in the mine plan, so the mineable resource base can be increased further by upgrading inferred resources to the measured and indicated categories.
In the zones near the mine, a company will focus on drill testing priority targets with the goal of delineating satellite resources to further expand the mine plan — which down the road could lead to increased production and an extended mine life. If the geological evidence warrants it, a company may also decide to conduct more grassroots exploration further afield using geophysical exploration techniques to determine potential drill targets. For example, copper porphyry deposits are famous for their large tonnage, high production rates and ease of mining. Within porphyry systems the copper mineralization can extend vertically for several kilometers beyond the main base of the open pit — often translating into a decades-long mine life.
The geological nature of the copper porphyry model also offers up a lot of exploration potential. This type of deposit is associated with alteration halos that are much larger than the deposit itself and can cover tens of square kilometers. The large scale of the mineralized system also lends itself to the formation of other types of deposits within the same area, including high-sulfidation epithermal gold — silver -copper deposits — increasing discovery opportunities and improving the economics of the mine plan.
This had the advantage that the variation distributions did not have to be estimated in the same units as those in the model. The normalised distribution was then multiplied by the base value for the corresponding input for the base year, derived from the larger LMP model, to generate a distribution for the input in the base year. The managers providing the distribution estimates were asked how the range of outcomes might change over the life of the mine, but no one identified any changes of this kind and we assumed consistent variations through time.
The same normalised distribution was multiplied by the base values for the other years over the horizon of the LMP, to generate distributions for the inputs in those years. The assumption is that the variation in each input is the same, in percentage terms, over the life of the mine and the LMP. Sources of information for risk variations and base values were recorded to facilitate validation and testing of assumptions. The volume of ore processed by sulphide circuit SC and its average head grade are inversely related for large changes in volume, linked to major expansion of mill capacity.
For marginal changes, volume and head grade are effectively independent. The volumes of ore processed by sulphide circuit SC and the roaster are positively related. Based on current experience, the observed sulphur content is relatively stable, so an increase in SC throughput is reflected in an increase in roaster throughput, but this relationship may change in future. A correlation of 0. Utilities costs are a component of the fixed and variable costs of the milling circuits and of the underground mining costs.
They are an insignificant component of open pit mining costs. The variation in utilities costs induces a small positive correlation between these items, but this was so small that it was not included in the model. No year-to-year correlation was included except for depreciation and amortisation, where a correlation of 0. The package Risk was used to simulate the effects of the risk variations on the main outputs required for making decisions.
The diagrams show the kinds of outputs that were obtained when information from the physicals analysis for the base year was included in the model. Figure 3 shows the net present value of the mine's cash flows in density histogram form, normalised for commercial reasons.
Figure 4 shows the same information in cumulative form, from which it is possible to determine the probability of achieving any specified NPV target value — as the target increases, the chance of attaining it decreases.
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Figure 5 shows the main drivers for the operating cost per ounce, in the form of a tornado graph. The graph shows the correlations on the horizontal between the input distributions on the vertical axis and the simulated distribution of operating cost per ounce. Positive values indicate the distributions move in the same direction both positive or both negative , while negative values indicate an inverse relationship.
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The main drivers for operating cost per ounce are the volume of ore milled in the SC circuit and the associated head grade, with operating cost per ounce reducing as throughput and head grade increase, an inverse relationship as indicated by the negative correlations. Other aspects of the processing circuits are also important.
Overall, mining costs seem relatively minor drivers of operating costs for this operation. Figure 6 shows how annual operating cost per ounce varies through the life of the mine plan, with the ranges of uncertainty for each year. The increase in costs in later years is associated with the changing characteristics of the ore available as mining progresses through the ore body. Some discussions were held concerning:.
Issues that were considered are shown in Table 4 and Table 5.
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The closure of D-North noted in Table 5 was modelled as a probability tree structure linked to minable reserves. This had relatively little impact on the mine plan. Global issues that were discussed in outline only are shown in Table 6. There may be a reduction in recovery as throughput increases, and an increase in the variability of recovery due to the increased difficulty in identifying problems.
This issue was to be discussed further. This was not considered likely in the near term, and alternative technology was not included in the budgets. This was likely within 2 years. It would add 0. The concession owners treated this outside the main LMP. For the operator, the gold price assumption for the LMP was specified by the owners' treasury function, as it depended on the combined forward sales hedging position of the consortium. The mine areas were well established, and a good relationship existed with the indigenous owners.
No claims were anticipated. Changes to development and fuel rebates were possible but unlikely. The owners had held discussions with Government, taxation and regulatory agencies and no immediate impacts were anticipated. The model developed a set of outputs that were important inputs to planning for both the operator and the owners. Plans that depended to a greater or lesser extent on the LMP included:.
There were significant additional benefits for the participants in the risk analysis too. By requiring the development of scenarios with quantitative estimates of the main operating parameters of the mine and mills, the modelling exercise forced managers to think in detail and with some numerical precision about their areas of responsibility. They had to do this as a group and reconcile their individual views with those of their peers. This had some interesting and, for the participants, unexpected benefits.
Managers' awareness of their own areas was enhanced, as was their understanding of the relationships of different parts of the operation to the overall operating outcome. Of course, they were all experienced managers and they had a high level of implicit understanding in any case, but they commented that the focus on numbers provided additional insights and a different perspective that they found valuable.
By considering responses to potential variations in the scenario-development process, managers started to think more explicitly about the value of flexibility in their operating areas. In particular, their individual plans reflected additional measures designed to position their areas for greater responsiveness when confronted by unexpected variability and change.
Overall, senior management found that the combined effects of these revisions to individual plans and the associated discussions contributed a lot to greater strategic organisational preparedness. The sponsor for this risk analysis reported a significant cultural change as a direct consequence of this exercise. Managers who had initially been cynical about the value of a supposedly 'theoretical' activity developed an appreciation of the detailed operational base on which the models were constructed and the additional insights that were generated.
One in particular became a strong advocate for the risk management approach — from an initial negative position, he became a champion for the introduction of targeted quantitative analyses for other aspects of mine development and expansion planning.
The model developed a set of outputs that were important inputs to: Capital investment plans for the operator, and funding plans for the owners Long-term capital structure and funding analysis for the owners Hedging strategies for the owners and their treasury functions. The Life-of-Mine Plan The operator was required to update its Life-of-Mine Plan as part of its obligations to the consortium that owned the concession. Approach and base model The general approach to risk analysis was extended, for application to the mine plan, to include more detailed quantification Figure 1.
The process began with a base model, containing no probabilities. In this case, the model was the Excel spreadsheet used for the mine plan. It was large, incorporating a number of Excel workbooks and significant detail, not all of which was needed for risk analysis.
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