The Ultimate Pit Analysis - What the graph is actually telling you!

The Ultimate Pit Analysis - What the graph is actually telling you!

At specific economic, production and engineering parameters/assumptions, pit optimisation solutions such as Datamine’s Studio NPVS outputs a graph which indicates the project value at specific, progressive pit sizes known as nested pitshells. Figure 1 below illustrates a typical graph of the Net Present Value with the corresponding size of the pit (tonnes).?

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The nested pit shells are produced through a process known as pit limit parametrization through the use of revenue factors. A revenue factor is a variable which when multiplied with other pit optimisation parameters such as metal price, will produce the different nested pit outlines at different factoring. Nested pit shells are always in the order of the highest to lowest value per tonnes mined. The sequence in which the growth of the nested pit shells progresses over time represents the optimal evolution of the mine over time.

The smallest nested pit outline represents the most robust pit i.e., a pit that will be economically viable even under the worst economic conditions.?Figure 2 below shows the smallest nested pit outline for a gold-copper deposit.The smallest nested pit guides the mine planning engineer to the portion of the deposit that should be extracted first since it remains financially attractive even after being penalised by a low revenue factor. ?

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The larger pits outline represents the pit with the longest life under the best economic conditions. This is shown on Figure 3 below:

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The Lerch-Grossmann nested pit shells can be interpreted as a method of incorporating risk aversion into the mine planning problem They help mine planning engineers know where to begin mining and what sequence to mine the pit in order to produce the highest NPV from the material within the final pit. At this point, it is important to differentiate between sequencing and scheduling. Sequencing refers to the order in which mining blocks are removed from the pit. When the geological model is kept the same, the evolution of the pit through nested pit shells will always be the same under different economic conditions. Scheduling involves determining the timing of specific mining activities.

For any deposit under specific economic, production and engineering parameters/assumptions, pit optimisation solutions will output the “Best Case NPV” and the “Worst Case NPV” as shown on Figure 4 below.

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The best case NPV occurs when each of the nested pit shells are mined one after the other, maximising NPV by mining ore as early as possible while deferring waste mining. The worst case NPV occurs when the final pit is mined bench-by-bench, from top to bottom, mining each bench completely before moving to the next bench. The difference between the NPV generate by the best case and the worst case determines the feasibility of, or an opportunity to add a pushback or two to the pit optimisation problem ??. The implementation of a pushback should be investigated. Remember that a pushback is nothing but a series of nested pits that conform to not only the minimum pushback width, but helps the schedule to provides the highest dollar value. As discussed previously, pushbacks need to be able to address the following critical points:

  • Geotechnical variables
  • Quality and size constraints

If the NPV generated by the best case and the worst case differ slightly, the implementation of a pushback will not add value to the project. The mining sequence for that particular pit is unimportant from an economic point of view.?

Most of the time, organisations target the pit outline with the highest NPV when running the Life of Mine plan. However, NPV is not the only way to evaluate mining projects. Sometimes the optimal pit for a specific scenario may be the one that maximises some of your corporate goals. It is important to keep that in mind as your go through the pit optimisation proces.

Nokubonga Thandeka Mabuza

BSc. (Hons) Industrial Engineering

3 年

How can we sort the problem of imbalance with the Milawa NPV scheduling but without trading in much value like the Milawa Balanced algorithm. I am using Whittle to do the optimisation.

Mario Fernando Mantarí Martínez

Data Analytics - FMS Administrator MS4M | Data Science & Machine Learning Enthusiast | Python Programming | IA Enthusiast

3 年

This is a really interesting pit-pit graph. When I was in the university, I coud learn about one method form my Professors but now I'm still studing and investigating about more ways to calculate the Ultimate pit by mean pit-pit graph. I would dare to say, the Ultimate pit would might be betwen 0.8 to 1.2 value revenue factor because from that pint, exists a small decline on the contour. And of course Net Present Value (NPV) begins to decline too. So, It'd no longer profitable. I'll be wait for your recommendation. Thanks so much.

Terence Makacha

Senior Mining Engineer | Mine Planning| Mine Design & Scheduling

3 年

Teach us, what’s the difference between scheduling and sequencing?

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