Pit Optimization – How I View It

One of the first steps in open pit mine design is the completion of a pit optimization analysis.  Pit optimisation is used to define the most profitable pit shell (or nested pit shells) for a given set of economic parameters.  The economic parameters generally include the metal prices, process recoveries, and operating costs. Normally when optimization is done, a range of metal prices or revenue factors is used to develop a series of nested shells to understand how the mine will expand or shrink with increasing or decreasing metal value.

Once optimization is complete, the mine engineer will design a pit with benches and ramps that mimics the optimized shell as closely as possible.

Depending on the slope angles used in the original optimization and where the  engineer positions the haul ramps, the pit design may or may not very closely resemble the original shell.  So the actual tonnage mined will be different that the tonnage defined by the optimizer.

Various experts in pit optimization will use approaches of differing complexity.  Some may apply variable mining costs with pit depth; apply variable recoveries link to head grade; apply variable pit slopes; etc.   One can make the pit optimization step as simple or as complex as one wants it.

The question is whether complex pit optimization is warranted.  My view is that overly detailed pit optimization is likely not required, other than if someone wants to test the impacts of parameter sensitivity.

Pit Optimization Has Many Uncertainties

A few of the uncertainties related to the optimization process are described below:

• Pit optimization can generate large pits that would have a long life.  However one doesn’t know the metal prices in the future, so think about the need for high accuracy for the initial optimizations.

• Pit optimization is done at the start of a study, so one has not even done the detailed operating cost yet.  Therefore one has to use rough estimates for costs and possibly even preliminary process recoveries.

• Operating costs will change in the future, and the optimization is just a snapshot using current information.

• The nested smaller pits, if developed, would likely be smaller operations and have different operating costs than assumed in the original optimization.   Similarly some of the larger pits may have different throughput rates and  operating costs than assumed in the optimization.

• The ore and waste tonnages reported within the pit will be based on a specific life-of-mine cutoff grade, which again has the fixed metal price and operating cost assumptions factored in.

• Overall pit wall slopes may differ for shallow pits versus deep pits.  Slopes may vary above the groundwater table and below it.  In many instances during pit optimization the wall angles are maintained the same irrespective of the pit depth.

• Dilution may be applied globally during pit optimization unless one is working with a diluted block model.  In reality, dilution may differ in different parts of the ore body, and that may not be considered in the optimization stage. For more discussion on dilution in general, read the blog “Ore Dilution Prediction – Its Always an Issue“.

Conclusion

The bottom line is that pit optimization should be viewed as a guide to the pit design, but not as a highly precise calculation.   Having said that, one should definitely understand how foreseeable changes in metal price will impact on the pit size, and then determine whether practical pushbacks are possible should metal prices increase.

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