April 2016

Integrated mine planning

  • By Peter McCarthy HonFAusIMM(CP), Director, AMC Consultants Pty Ltd

Examining the importance of designing the metallurgical plant within the context of the broader optimisation of the mining project

The mine planning process includes the mining, processing, infrastructure, environmental and social aspects of an operation. It begins with a sequence of increasingly-detailed feasibility studies and continues throughout the life of the mine through several long-term and short-term planning processes.

At various points in the sequence of mining and processing activities there is a need to choose a particular value of the value descriptor, called a cut-off, to enable decisions to be made about what to do next with raw or semi-processed material. Selection of appropriate cut-offs is an outcome of the mine planning and optimisation process. While approximate cut-off grades may be used early in the resource estimation process, these are superseded by better, value-maximising cut-off grades as planning progresses. The process is iterative and cut-offs are influenced, among other things, by the chosen mining and processing rate. The two variables, cut-off and mining/processing rate, are the primary levers that can be used by planners to optimise the mining and processing plan.

Historically many mine developers did not have ready access to project capital and so they had to develop projects using a combination of new shareholders’ funds and retained earnings. More recently there has been an assumption that any scale of project will attract project finance if it satisfies the hurdles set by bankers, so capital constraints are not commonly included in the project optimisation process. Bigger projects are generally thought to be better. In reality, the interests of existing shareholder owners of a mineral deposit may be best served by a modest scale of development, with restricted use of external capital. The value of a smaller project as measured by net present value (NPV) may be lower, but the risk-adjusted value to existing shareholders may be greater.

Mining rate limitations

There are physical limits to the rate that any orebody can be mined. High rates of mining are associated with greater day-to-day or month-to-month production volatility, with a tendency for dilution of the ore to become excessive at high rates as the pressure of production reduces the ability to mine more carefully and selectively.

The floor of an open pit can be advanced quickly but, as a rule of thumb, the open pit production limit is around eight benches per year, or 80 m vertical advance using ten metre benches, though some very large pits and small, short-life gold pits can achieve over 100 m per year within the operating area. However, an average sink rate of 40 m to 60 m per year is more likely for longer term planning in most pits. Once the vertical advance rate is established, the average production rate can be determined from the available tonnes of ore per vertical metre (tpvm) within the pit design.

Similar considerations apply to underground mines. The production rate from an underground mine is not usually limited by the rate at which decline development can be advanced, but by the number of available working faces, which in turn depends on the amount of pre-development, possible rates of ongoing lateral development, infill drilling, stope turnaround times, backfilling and so on, with interference between these activities.

In steeply dipping deposits underground mining can occur on several levels simultaneously, but the mine production rate can still be related to the ore tpvm that will be mined. This relationship can be expressed as the ‘effective vertical advance rate’, or the relationship between actual mining rate and the tpvm available in the deposit. The risk of failure increases as the vertical metres per annum (vmpa) increases. In a 2014 study of 12 current Australian mines using sublevel open stoping methods, the author found that average vertical advance rates varied from 23 to 71 vmpa with an average of 43 vmpa, while the maximum single-year rates varied from 31 to 79 vmpa with an average of 56 vmpa. Only one mine sustained a rate higher than 61 vmpa. As a generalisation, special circumstances are required for any underground mine to sustain a rate above 60 vmpa.

The optimum rate can only be determined after detailed scheduling of alternative mining plans and the completion of an optimisation study that balances risk and revenue against capital and operating costs for the entire mining and processing operation.

Mining flexibility

Mining engineers are fully absorbed in meeting existing challenges and have limited capacity to vary the method and sequence of mining to deliver a better or more predicable product to the process plant. Monthly, quarterly or annual mining schedules are based on the ore reserve model, which is frequently found to be deficient at those scales. Changes to the mining sequence are made on the run, and the challenge for the mining engineer is to deliver the scheduled tonnes, of any quality, above the mining cut-off.

Some mining methods allow no short-term control of product quality, while others are more flexible. The best way to achieve predictable feed for the process plant is to develop an accurate orebody model in which all of the variables of consequence are modelled faithfully, and to set the mining rate low enough so that selective mining can be practiced on every time scale. This requires competence in the emerging specialty of geometallurgy, a healthy geological budget for drilling and modelling, and an uncommon appreciation of the benefits of mining at a rate lower than the maximum possible.

Production volatility refers to the relative variation in a parameter from one time period to the next. The volatility of parameters such as feed tonnage, head grade, metallurgical recovery, throughput or product output can be measured hourly, daily, monthly, etc. The more volatile the measure, the less use is being made of the installed capacity and hence of the capital invested and of the fixed component of operating cost. One of the key symptoms of a system that has been pushed beyond its stable capacity is an increase in production volatility. The specifications for the processing plant should reflect real hourly or daily mining outcomes, not a smoothed and idealised schedule. Volatility can be reduced by the use of stockpiles.

Ore stockpiles

Today many mines are designed without significant stockpiles. Block caving mines in particular may have no effective stockpile capacity between the draw-point and the surface stockpile. Even the surface stockpile may be eliminated in normal operation, with the inclined conveyor from the underground mine delivering crushed ore directly to the secondary crusher. In these circumstances the miners have no ability to manage product quality. In many other operations, such as sublevel open stoping or longhole retreat stoping without shaft hoisting, the old approach of using ore-passes as stockpiles has been eliminated and ore is hauled to the surface in trucks. This provides an opportunity to manage ore quality by blending using two or more dump points at the run-of-mine (ROM) stockpile. Management of ore quality then becomes the responsibility of the reclaim operator, but may require resampling to establish the variability and location of material within the stockpiles.

The more challenging the mining situation, the greater the stock levels need to be including developed (exposed) ore stocks, drilled stocks, broken stocks, and ROM pad stocks. If these stock levels are adequate then volatility can be reduced to a minimum. The mine should be designed so that all stockpiles, including orepasses in an underground mine, have adequate capacity to smooth the short-term surges to a level acceptable for the system as a whole, including ore processing. This is a commonly overlooked requirement.

The reliability of mining equipment has an effect on ore quality. Delays in mine development (accessing ore in an underground mine or pre-stripping in a pit) can lead to periods when low-grade or high-impurity ore is all that is available. Breakdowns in ore-production equipment can lead to increased dilution, because it is human nature to be less concerned about dilution when there is insufficient ore available to feed the mill. Proper mine design, planning, scheduling and maintenance require good management. Ultimately, the capabilities of the mine management team will determine the quality and regularity of mill feed.

Processing rate

A plant of any capacity can be built, at a cost, although there are step-changes in the capacity of available components that make particular rates more attractive. The availability of services such as power or water may place an absolute limit on the size of plant, or impose a large capital cost burden for going beyond that point.

Once a plant is operating, the processing rate may be limited by feed characteristics. For example, harder ore than expected may limit the milling rate while wet, clayey ore may limit the crushing rate. For these reasons plant components and the overall plant capacity may be oversized to some extent as compared to the selected mining rate. If this is recognised by management as an allowance for variable ore quality then no problem arises, but invariably when the ore quality is good the higher capacity is pushed back to the mine as a demand for a higher mining rate, with adverse consequences.

Predicting feed quality

A resource model based on exploration drilling only is used to design a mine at the feasibility study level, with their predictions of mining dilution and mining recovery used to estimate an ore reserve. The mining schedules produced in the feasibility study are used by the plant engineers and metallurgists to design the plant. At this stage there may be a very poor understanding of the hourly, daily or weekly variability in ore quality or of the distribution in space of valuable material, process contaminants, ore hardness and so on. At best, the mining schedules are presented as monthly averages for the initial few years and as quarterly or annual averages thereafter.

As initially constructed, the processing circuit must be designed to cope with or be adapted to the expected range of ore qualities, with an ability to respond quickly to any changes. Alternatively, with a less flexible circuit, the cost and revenue impacts of possible variations in ore quality must be examined to ensure they fall within acceptable limits. The impact may be greatest in the first year, when orebody knowledge is weakest and cash flow is critical.

The planning process begins with a good three-dimensional geological (resource) model. Geological domains are identified such that a common set of rules can be applied to determine local variations in metallurgical responses within each domain. The domain boundaries may be structural, mineralogical, alteration or lithological. Poor geological modelling and domaining are the leading causes of failure in geostatistical modelling for grade estimation and for modelling metallurgical parameters.

Domains should be defined beyond the ‘orebody’ to include all material that could find its way into the ore stream. Metallurgically, adjacent domains may have little or nothing in common. Samples representing each domain can be subjected to laboratory-scale test work to determine the rock’s resp7onse to each mineral processing operation. The geostatistical approach used to model metallurgical performance need not be complex. However, the more advanced geostatistical methods are not difficult to apply. Selection of the best techniques is the subject of ongoing research.

Samples for metallurgical testing are usually composited from diamond drill core, which may be of limited availability for some domains. Large metallurgical samples excavated from near the surface of a deposit are unlikely to be representative of the orebody at depth. Shafts sunk for the purpose of obtaining large metallurgical samples may also yield unrepresentative samples, or samples that represent performance in only one domain.

Due to the shortage of material for testing, it may be necessary to develop local correlations between metallurgical test results and other properties such as point load strength, rock quality designation (RQD), fracture frequency and mineralogy in order to obtain sufficient data to create a meaningful three-dimensional model. In the end, the variability of factors affecting metallurgical performance may occur at a scale smaller than can be economically sampled, so the process plant must be designed to cope with volatility.

Optimising the mine and processing plant

The key parameters over which a mining company has control are the size of mine (large or small, low or high grade, as determined by the cut-off grade), the mining method, the production rate, the mining sequence, the processing method and the amount of money that will be spent on getting these things right, which includes exploration drilling, geological modelling and bench and pilot-plant testing. Other aspects such as power supply, water supply, concentrate transport and logistics generally have a more obvious engineering solution and are ancillary to the optimisation process.

The objectives of optimisation must be aligned with the corporate objectives of the owner. Some stated corporate objectives, such as maximising annual ounces of gold production or maximising mine life, cannot be optimised. Clearly, increasingly large sub-economic projects will satisfy the former objective while decreasingly large sub-economic projects will satisfy the latter. Short-life projects carry the risk that most of the production will be delivered into a trough in the product price. Sensitivity analysis based on a range of price scenarios will identify the parameters that yield an acceptable risk.

There is also the problem of capital allocation between competing projects. If there is no restriction on the available capital, then corporate value is maximised by maximising the NPV of every available viable project and carrying all of them through to production. In the real world, where available capital is restricted, the corporation must select projects for investment using some ranking technique. Economic theory says that projects should be ranked using the present value ratio (PVR), which is the ratio of NPV to initial capital investment.

From the above, the project should be designed to maximise the project NPV at the corporation’s agreed discount rate, provided that this leaves it with a PVR that will make it an attractive investment. Arguably, the plan should be changed to improve the PVR, even at the expense of NPV, if this will allow the project to proceed in competition with others.

Managing the downside risk

The need to manage risk was well understood in the past. A small project was built, often with second-hand plant, and then cash flow from the operation, or equity funding from the now-reassured investors, was used for a series of expansions and optimisations. If there was a problem with the initial ore reserve or cost estimates, the exposure of shareholders to this problem was minimised and managed.

The value at risk (VaR) approach, widely used in the financial sector, may be useful when making large investment decisions. VaR is the maximum loss not exceeded with a given probability defined as the confidence level, over a given period of time. It is commonly used by security houses or investment banks to measure the market risk of their asset portfolios (market value at risk), over time periods of one day to a few days. However VaR is a very general concept that has broad applications.

For example, a Monte Carlo approach to modelling net cash flow outcomes for a particular project development option might show that 95 per cent of outcomes have a net cash result better than minus $50 M. In other words, the cash loss is expected to be greater than $50 M only five per cent of the time. This approach must have a constrained time period applied, such as the time to project payback or a fixed number of years. The various project development options can be modelled and a decision made based on both the expected NPV and the VaR for each development option. Ultimately, the corporation must be able to absorb and manage the ‘worst case’ outcome.

Conclusions

The design of metallurgical plant should be undertaken in the context of the broader optimisation of the mining project. Often the appropriate metallurgical process can be selected early in the optimisation process and thereafter the plant design is simply a matter of good engineering, without strategic options. By contrast the size of mine (large or small, low or high grade, as determined by the cut-off grade), the mining method, the production rate and the mining sequence are strategic decisions that form critical inputs to the engineering design of the metallurgical plant.

In recent years many project investment decisions have been made on the assumption that unlimited project finance is available. Due to global economic circumstances this is no longer the case, and a more traditional approach to project optimisation is called for. After consideration of risk, a modest-sized, staged development may provide better shareholder returns than the largest project that an orebody can theoretically support. Staged development may require multiple parallel processing circuits and smaller, more selective mining machines operating at higher cut-off grades.  

A version of this paper was originally delivered as a keynote presentation at the MetPlant 2015 conference.

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