Over my years of preparing and reviewing mining studies, ore dilution often seems to be a contentious issue. It is deemed either too low or too high, too optimistic or too pessimistic. Everyone realizes that project studies can see significant economic impacts depending on what dilution factor is applied. Hence we need to take the time to think about what dilution is being used and why.
Everyone has a preferred dilution method.
I have seen several different approaches for modelling and applying dilution. Typically engineers and geologists seem to have their own personal favorites and tend to stick with them. Here are some common dilution approaches.
1. Pick a Number:
This approach is quite simple. Just pick a number that sounds appropriate for the orebody and the mining method. There might not be any solid technical basis for the dilution value, but as long as it seems reasonable, it might go unchallenged.
2. SMU Compositing:
This approach takes each percent block (e.g. a block is 20% waste and 80% ore) and mathematically composites it into a single Selective Mining Unit (“SMU”) block with an overall weighted average grade. The SMU compositing process will incorporate some waste dilution into the block. Possibly that could convert some ore blocks to waste once a cutoff grade is applied. Some engineers may apply additional dilution beyond SMU compositing while others will consider the blocks fully diluted at the end of this step.
3. Diluting Envelope:
This approach assumes that a waste envelope surrounds the ore zone. One estimates the volume of this waste envelope on different benches, assuming that it is mined with the ore. The width of the waste envelope may be correlated to the blast hole spacing being used to define the ore and waste mining contacts. The diluting grade within the waste envelope can be estimated or one may simply assume a more conservative zero-diluting grade. In this approach, the average dilution factor can be applied to the final production schedule to arrive at the diluted tonnages and grades. Alternatively, the individual diluted bench tonnes can be used for scheduling purposes.
4. Diluted Block Model:
This dilution approach uses complex logic to look at individual blocks in the block model, determine how many waste contact sides each block has, and then mathematically applies dilution based on the number of contacts. Usually this approach relies on a direct swap of ore with waste. If a block gains 100 m3 of waste, it must then lose 100 m3 of ore to maintain the volume balance. The production schedule derived from the “diluted” block model usually requires no subsequent dilution factor.
5. Using UG Stope Modelling
I have also heard about, but not yet used, a method of applying open pit dilution by adapting an underground stope
modelling tool. By considering an SMU as a stope, automatic stope shape creators such as Datamine’s
Mineable Shape Optimiser (MSO) can be used to create wireframes for each mining unit over the entire
deposit. Using these wireframes, the model can be sub-blocked and assigned as either ‘ore’ (inside the
wireframe) or ‘waste’ (outside the wireframe) prior to optimization. It is not entirely clear to me if this approach creates a diluted block model or generates a dilution factor to be applied afterwards.
When is the Cutoff Grade Applied?
Depending on which dilution approach is used, the cutoff grade will be applied either before or after dilution. When dilution is being added to the final production schedule, then the cutoff grade will have been applied to the undiluted material (#1 and #2).
When dilution is incorporated into the block model itself (#3 and #4), then the cutoff grade is likely applied to the diluted blocks. The timing of when to apply the cutoff grade will have an impact on the ore tonnes and had grade being reported.
Does one apply dilution in pit optimization?
Another occasion when dilution may be used is during pit optimization. There are normally input fields for both a dilution factor and an ore loss factor. Some engineers will apply dilution at this step while others will leave the factors at zero. There are valid reasons for either approach.
My preference is use a zero dilution factor for optimization since the nature of the ore zones will be different at different revenue factors and hence dilution would be unique to each. It would be good to verify the impact that the dilution factor has on your own pit optimization, otherwise it is simply being viewed as a contingency factor.