This chapter has described the data requirements and procedures to perform a strategy optimisation in detail. It is not possible to fully optimise the mining strategy without considering the metallurgical treatment processes and vice versa. A full strategy optimisation requires an integrated evaluation of all parts of the production process across the whole life of the operation.
The corporate goals must be borne in mind throughout the optimisation process. They indicate what is required to derive value measures for those goals, and the processes and data to do that. As well as goals, it is vital to identify all the options to be evaluated; data and relationships must support the full range of values.
It is necessary to take account of the influences of uncertain parameters in an optimisation study. As with the most uncertain parameter in a mining strategy evaluation, the product price, it’s the norm to estimate the most likely scenario and flex the price inputs over a range. A change in price or any uncertain input will change the value of any operating plan, but the issue is not the absolute value, but how changes might cause the optimum plan to vary. If the decision-changing situation is found to be outside the likely range for an uncertain parameter, it may be important for defining the value, but not the optimum strategy. If it lies near the most likely value or relationship, steps must be taken to reduce the uncertainty or consider the trade-offs between the benefits and costs of making decisions based on the right or wrong assumptions.
Following is a summary of the types of inputs and processes typically required.
Geology
The major activities related to geology for an optimisation study are: • create a reliable model for the range of cut-offs to be investigated • generate potential orebodies at each cut-off
• identify domains that require different mining methods, scheduling constraints, metallurgical treatment, etc.
If the model is unreliable for some cut-offs, rigorous analytical processes can still be conducted using the existing model. If the optimum strategy is then found to lie within the range of cut-offs where the geological model is deemed to be reliable, the identified optimum will be reliable. If, however, the optimum strategy lies outside the reliable range, identify the best value within the reliable range, the additional value potentially available, and whether that justifies the cost of extending the reliable range of the model.
Mining
The major activities related to mining for an optimisation study are: • identify suitable mining methods
• create realistic mining shapes and aggregated mining blocks, and hence reserves for each cut-off or pit limit and mining method
• produce conceptual mine designs and schedules for selected representative cases (for model calibration)
• aim to maximise the information obtained while minimising the work to be done • develop suitable interpolation relationships for other cases.
For open pits, the aggregated mining blocks will be bounded by pit shells corresponding to each major pushback stage and by a number of elevations, spaced at a multiple of the bench height. The optimisation software will select the blocks that are to be mined and schedule them in such a way as to generate the ultimate pit size and optimum mining sequence. It will usually be necessary to define haulage distances for each mining block to both ore and waste-dumping points. The optimisation will decide what is ore and what is waste, so both distances need to be available to the optimiser. More complex information may be required depending on dump locations, rock types and the like.
Underground, mining blocks will typically be defined by a combination of ore zones, sublevels, northings or eastings, geological structures, changes in the size and shape of the orebodies and boundaries defining geological domains within the rock mass or
CHAPTER 8 | The Mine Strategy Optimisation Process orebodies. The mining inventory for each cut-off must take account of both the ore loss and dilution to generate realistic stope designs and the elimination of outliers of material above cut-off that would be uneconomic to extract.
Development requirements for each underground mining block will be needed. It may be relevant to specify what proportion of each category needs to be completed before the mining block can start producing. Trucking distances may vary if different haulage and hoisting options are to be evaluated. Quantities of backfill of various types may need to be specified if mining methods being evaluated have different fill types or proportions of the orebody to be filled. Underground data requirements may also include such items as access methods or topologies.
Scheduling rules need to be specified for both open pit and underground optimisations.
Processing
The major activities related to processing for an optimisation study are:
• specify recovery relationships for the range of cut-offs and hence feed characteristics to be evaluated
• identify constraints and how to remove them for the ore and all product streams • determine the impact of debottlenecking on recovery, product quality, operating and
sustaining capital costs, etc.
Because of the wider range of feed characteristics modelled in an optimisation study, better relationships may need to be developed for the study than those used in the operation for a narrower range. Scenario analysis may be necessary over any uncertainty range in the relationships to identify whether strategic decisions will change if relationships vary. The increasing focus on geometallurgical properties of mineral resources leads to greater information being taken into account to optimise operating strategies. This potentially increases the complexity of the analysis to account for it.
Operating costs
A suitable cost model is required, typically incorporating fixed costs (related to time elapsed) that do not vary across the range of activity levels evaluated, and variable costs driven by physical activities such as development metres (underground) or waste mined (open pit), ore tonnes mined, truck tonne-kilometres or operating hours, backfill tonnes (underground), ore tonnes milled and product quantities.
Capacity or step variable costs may be relevant. These are fixed across a portion of the whole range, with step changes at threshold levels of activity.
The general principle is that variable costs need to be specified separately for any physical parameter that does not vary in direct proportion to rock, ore or product quantities. An overall average cost per tonne will include costs associated with all parameters, assuming that the ratios of all quantities are unchanging. If the physical ratios change with changing strategies, the unit cost will as well. This introduces a circularity into the analysis, resolved by relating costs to the parameters that drive them.
The way in which unit costs are reported in company documents usually does not describe how they behave. The evaluation team must examine the cost data provided and, when necessary, reallocate or reclassify, to ensure that the cost model accounts for how costs actually behave.