Strategic mine planning - Finding the optimal mining strategy by evaluations
Reducing complexity of mining investments
The complexity of mining investment projects is considerable, and the overall evaluation of planned investment is considered extremely difficult. Initial data for strategic mine planning is crucial, and incorrect data can lead to very misleading judgements if not recognised in the evaluation process.
Thus, early-stage mine development should evaluate multiple different concepts for mine operations, in order to find the most optimal alternative for the entire mine lifecycle. But what aspects need to be taken into consideration when mining project evaluation is conducted in the early mining project development phase?
Mining strategy selection depends on the planned mining concept (open pit or underground) and deposits size as well as investors' capabilities, and how the mining operations are planned and implemented.
Large deposits require a series of multistage mining strategies and evaluations
Commonly, a multistage implementation approach of mining operations is developed if the ore deposit is large enough. Usually, multistage operations are initiated from a smaller starter pit with high cash flow, and later the pit is extended using pushbacks to a much larger pit. Likewise, waste stockpiling and tailings disposal areas are designed in stages.
Multistage mining strategies are commonly applied to ore deposits that have a high waste rock to ore ratio (lots of waste rock material requires excavation in order to access the “deeper” ore). In such cases, the underground mine trade-off can be compared to large open pit pushbacks. Multistage mining operations require a high level of engineering understanding of the technical and economic feasibility of the chosen mining concept.
At the more detailed strategy level, traditional strategic mine planning includes a series of multistep processes to evaluate the tradeoffs of different open pit scenarios. Typically, a detailed open pit plan is generated based on pre-analysed cut-off grades, with the intention of achieving desired goals, such as a target feed to the processing plant while maintaining a smooth material flow to simulate the operation of a mining fleet. A detailed open pit plan is then used to calculate mining equipment numbers, sizing of the processing equipment and operational hours. All of them are the main inputs to the operative cost models that calculate more detailed mining costs and overall economics already in development phase.
Initial parameters for mining investment evaluation - What is crucial?
Initial data for strategic mine planning is crucial, and bad data can lead to very misleading judgements if not recognised in the evaluation process. The most important and at the same also most “dangerous data” in the mine optimisation is geology, and how it can be processed in the minerals processing phase. If geology and processing data are incorrect, the whole optimisation goes wrong regardless of how accurate other parameters are. Geological and processing information given into the mine optimisation process must be understood and verified by more than one experienced and qualified geologist. Other parameters fed to the optimisation are rather simple due to their nature of being technical or economical parameters.
Geology being a descriptive natural parameter that is squeezed into numerical world and having lots of gaps and interpretations are commonly the faulty component that leads to incorrectly evaluated mining projects.
The failure to evaluate mineral processing recoveries or commodity prices pricing is equally critical to the overall assessment. Incorrectly forecasted metal or commodity prices may not be detected in the first 1-5 years of the mining operation, but they will be visible later in the project economics.
Global standards for reporting project evaluations
Global standards are intended to secure mining operators, investors, local communities and governments in making reliable mining project evaluations.
The most used international standards are JORC-code and NI43-101, which are more or less certificates of trust. Mining project evaluations prepared in accordance with such standards are trusted in the stock exchanges worldwide. The JORC-code and NI43-101 codes have a strong focus on the mineral resources and ore reserves that are derived from the geology. Standards classify mineral resources and ore reserves into classes depending on the accuracy of the geological investigations. For example, JORC-code classifies mineral resources into inferred, indicated and measured mineral resource classes. To have a reasonable amount of geological data to support the ore reserve estimate, ore reserves can only be defined from indicated and measured mineral resource categories.
10 golden advice for a successful mining project evaluation
- Objectives must be understood and communicated throughout the project team involved in the strategy process
- Correctly defined mine size will improve your project value and success
- Double check your metal price estimates and operational cost estimates and then double check them again with someone else
- Get the geology and processing of it right. Accept no assumptions. Garbage in, garbage out.
- Evaluate multiple scenarios and generate alternative strategies. Look through profitability but also the impacts. Review them, communicate them.
- Ore dilution and ore loss are your hidden enemies.
- Cut off grades can be assessed using Marginal Cut-Off and Operating Cut-Off
- Schedule your production according to the minerals processing. Optimised production scenarios can significantly improve your project´s NPV.
- Use modern software and cross check using multiple software / approaches.
- A single road on top of your ore body won´t necessarily kill your project but a natural preservation area might do so.
Open pit optimisation uses digital mining software
Open pit optimisation is a method for determining the most economically extractable form of an open pit based on the available input data. In open pit optimisation, the net present value, cash flow, and payback period of an entire mining project are calculated using a few mathematical models. Mathematical models such as the Lerch-Grossman algorithm and Direct Block Scheduling are mainly embedded in commercial software such as Deswik GO, Whittle or Minemax, etc. The mining software optimises the open pit mine production by utilising a geological model, minerals processing parameters, end product price estimates and project operating costs. The calculations can also be performed using other relevant information, such as the time dependence of the project, taxation and, for example, the time and cost impact on the environment. Calculations can be performed according to nominal or real costs depending on the estimation method and objectives of the estimation.
In open pit mining optimisation, mineralisation (geology) is described by a geological block model. The block model is a 3-dimensional database compressed into mathematical blocks in which the entire mineralization is defined. The blocks in the block model include mineral grade concentrations, production parameters and contaminant concentrations, operational operating costs, parameters related to ore processing, and all other information relevant to optimisation.
The open pit optimisation software progressively constructs a list of related blocks that should or should not be mined from the block model based on the block data. The final block list defines an ultimate open pit outline that has the highest possible NPV value or other targets in question while considering the required economical parameters, pit slope angles and other physical constraints.
Using the Lerch-Grossman algorithm for optimisation
In the Lerch-Grossman algorithm, revenue factors are used to define the final ore inventory and select the ultimate open pit. At a revenue factor of 1, the cash flow is maximized and hence also defines the ultimate pit size and shape. At lower revenue factors (<1) optimisation produces smaller pits with high grades but a reduced mine life. At higher revenue factors (>1) optimisation produces larger pits and longer mine life, but with reduced outcomes in profitability. In the end, everything is very simple and straightforward.
The optimisation produces pit shells that are later used in the open pit design procedure. In practice, open pit designs, haulage ramps, pit safety berms and bench slopes will change the shape of the optimized open pit shell. This will make changes to the reported ore inventory depending on how accurately the original pit shell was used in the practical pit design. The ultimate open pit is finally designed according to the rock mechanical stability parameters that are gained from separate rock mechanical studies including analysis and simulations.
This is Part 2 of the insight focusing on the mining strategy selection by using evaluations as a method. Part 1: Early phase concept development in mining operations focuses on the early phase of mine strategic planning including evaluation of different concepts for open pit and underground mines. You may also be interested in How to select the right Mining project implementation method?
On the author: Mikko Lamberg, Head of Mining & Metals, Finland.
Mikko has more than 13 years of experience in mining (design, mineral reserve estimation and rock mechanics) projects ranging from conceptual through feasibility design levels and operations support. He has undertaken and managed large strategic mine planning and rock mechanics projects for the mining industry in Finland and Nordics, having been mainly responsible of supervising design, quality and scope.
AFRY’s services for mining, minerals processing, and metal industry extend from preliminary exploration activities and environmental permitting to finished goods for use in further production, to end-of-life recycling. We offer a full range of consulting and engineering services to help mining and metals companies in shaping and developing their ideas and concepts into technically, financially and environmentally sound solutions. We can identify the optimal technological options for each project as we are completely independent of machine suppliers.