Part 1 of this article, in our last edition of Digging Deeper, asked “How do you optimize and maximize the value chain of your mining project?” and concluded that the key is to apply innovative thinking to bridge traditional one-discipline silos. Geometallurgy is the term used for this integrated approach, which depends on seamless cross-discipline collaboration to gather appropriate data, explore and evaluate options, and implement effective changes to operations. In Part 1, we considered the various inputs to the value chain, their functions, and the interrelationships between them. In Part 2 we present three mining scenarios based on real operations that illustrate how the Geometallurgy approach can be used to extract significant additional value from mining operations.
Case Study 1: Open-pit porphyry copper-gold mine – grade descriptor and waste management optimization
The orebodies contained several rock types with multiple styles of mineralization, containing different minerals, resulting in different recoveries, products and product qualities, plus differing acid-forming characteristics in the waste rock and tailings. Previously, the mine had used a copper-equivalent grade descriptor that combined all valuable components into a single copper grade to blend run-of-mine ore for maximum value. A better grade descriptor was developed that took into account multiple parameters in addition to ore grades that determine value. This descriptor expressed value per unit of constraint at the mill, the bottleneck of the overall process, which allowed targeting of the material that added the most value through the mill. For a mill, it’s the available hours, not the nameplate capacity that determines actual output.
The key ore parameters, including hardness, were combined into a “Net Revenue per Mill Hour” value descriptor, which resulted in a reassessment of where value really lay in the pit, determining the best mining sequence. It also fed into schedules, equipment requirements and costs, to help maximize the project’s value over the ensuing years.
The approved method of waste and tailings disposal for this project was riverine discharge, with associated environmental impacts and community concern. A set of tailings and waste disposal improvement options were developed, costed, and presented to environmental, community, and regulatory stakeholders for consideration. A consensus on the preferred improvement option was obtained, and the mining and processing aspects of the project were subsequently optimized. Specifically, pH adjustment and amelioration of potential acid formation in waste and tailings was instigated. Costs associated with neutralization (among other handling and disposal costs) were attributed to the block model according to pyrite content. Hence, tailings and waste disposal costs were included in the optimization process, with input from key environmental and community stakeholders.
Case Study 2: Open-pit gold – comminution parameters
The operation encompasses multiple related epithermal gold deposits and a conventional carbon-in-leach processing plant. Comminution is achieved using a single stage of crushing, followed by a SAG mill / ball mill / pebble crusher arrangement to generate leach feed with P80 of 150 µm. Over a number of years, multiple drilling campaigns and testwork programmes produced comminution data for up to nine ore types. The ore types varied widely in hardness, abrasiveness, and amenability to autogenous grinding. The design of the plant and the life-of-mine processing plan were based on the 85th percentile values of key comminution parameters for each ore type. While this is a conservative approach, many occasions have still arisen when the plant is unable to maintain instantaneous feed rates due to the hardness/abrasiveness of the ore type being fed. In addition, average throughput over time periods when multiple ore types have been fed has also been below design, as the plant and its operators have been unable to fully capitalize on periods when ore is softer and higher feed rates are possible. This has been primarily due to lack of sufficient notice that an ore type change is imminent.
Blending of run-of-mine ore to constrain feed to the comminution circuit within operating limits is an obvious remedy for the issue. Efficient blending will require development of an effective algorithm that allows operators to calculate the economic consequence of delivering any particular blend of ore to the mill. The algorithm requires the following elements:
- Established relationships linking economic value, plant throughput rate and recoveries to measurable characteristics of the ore.
- Sufficient measurements to characterize meaningful domains of the deposit.
- A current, well-maintained model that contains appropriate block data to allow mine planning on the basis of expected economic value to be derived from the run-of-mine blend delivered to the crusher.
- A system of reconciliation and model adjustment, to ensure the ongoing relevance and usefulness of the model as the mine develops.
Adjustments to the mine plan, and decisions involving blending of ore on the ROM pad would both be undertaken using the model. Some increase in operating cost, and perhaps some additional capital expenditure may be required to provide additional sources of ore at any given time, but such decisions will always be taken on the basis of increased overall economic benefit.
Case Study 3: Underground base metals – grade descriptor, mining method, production rate and cut-off optimization
The client operated an underground lead-zinc mine and was seeking to generate better returns. Historically the mine had been developed as a sequence of mining blocks approximately 100 m high, with deeper blocks opened up as those closer to surface were depleted. There were known sub-vertical trends in grades, but the orebodies defined using the existing metal equivalence formula and cut-offs were such that the “grades” seen within the mineralized zone were relatively homogeneous along strike. The bulk of the mineralization was mined out using open stoping with backfill to facilitate close to total extraction, with only a few lower grade pillars being left in situ between the major lenses. The mining sequence was therefore predominantly along-strike, with a subsidiary advance from top to bottom. Recovery of the crown pillars created between lifts presented technical challenges, with both lower productivity and reduced ore recovery in those areas.
The grade descriptor in use at the time was a simplistic equivalent metal value proxy for true block value, which took no account of the different recoveries, payabilities, metal prices, or realization costs associated with each metal. At that time, building full Net Smelter Return relationships into the block modelling software was not feasible, so AMC worked with the key site personnel to identify and apply appropriate recovery versus grade relationships and sales terms, to derive “true” values for each block. For a representative sample set of grades, the “true” values were regressed against the input grades to obtain a set of multipliers to give the statistically best linear relationship between grades and value. A revised equivalence formula with a much lower variation in true value for any given equivalent grade value was adopted, resulting in better correlation/reduced scatter between the grade descriptor value and true value as shown in Figure 1.
Figure 1 Case study 3: Changes in spread of true values with different grade descriptors
When the mineralization was viewed using the new grade descriptor, the vertical zonation, particularly at higher cut-offs, became more pronounced. An obvious change to the mining method was to develop immediately to the bottom of the deposit and establish stopes extending over the vertical height of the remaining orebody, with mining in a predominantly bottom-to-top sequence within lenses, and a subsidiary advance along strike. This permitted both the elimination of crown pillars, and the establishment of extra vertical rib pillars between stopes in lower value material, allowing a significant reduction in the amount of cemented fill required. The overall value of the resource was enhanced by reducing the misclassification of ore and waste, due to the better correlation between the grade descriptor value and “true” value, given that the cut-off is applied to the grade descriptor value in the block model, and not the (unknown) true value.
Figure 2 shows value versus cut-off for both the original equivalence formula and mining method, and the revised equivalence formula and mining method. The values for the latter include the effect of earlier capital development to drive immediately to the bottom of the mine to establish the full-height stopes.
Figure 2: Case Study 3: value increase from grade descriptor, cut-off and mining method changes
The production rate also had a significant influence on value. Although the mine’s target was nominally the same as the concentrator capacity, and the fleet size and workforce numbers were in place for this, the mine was in practice delivering only some 85% of that target. It was identified that there were inadequate stock levels of developed and drilled ore, exacerbated by the reliance on a small number of large stopes in operation at any time. Additional value could be gained simply by producing at the target rate. This could be achieved by injecting working capital to increase ore stocks, and producing from a larger number of smaller stopes. The change in mining method also facilitated this change. Additional capital investment to upgrade the capabilities of the rock handling systems was thereby avoided.
The client elected to change the mining method and to increase the cut-off substantially towards the identified optimum, so as to realise the bulk of the identified potential gain, while at the same time limiting the reduction in ore reserves to a level where it believed the market would not react adversely, and perversely drive the value of the shares down despite the increase in value generated for shareholders.
Part 2 of the Geometallurgy story has presented three sample scenarios based on real projects that illustrate how the Geometallurgy approach can be used to extract significant additional value from mining operations.
The collection of appropriate key data input parameters is fundamental to the success of a Geometallurgy approach. Important factors that AMC has observed in working with client projects include:
- Most of the data often exists already in some form or another – don’t be concerned that there will be additional significant costs associated with developing a programme to obtain the data.
- Data in the wrong form is still useful and/or useable – data in the wrong form or incomplete data can still be adapted and ‘flexed’ to provide value to the overall process, identify its impact on value and, more importantly, on decisions, to indicate how critical it is to get the extra information.
- For new projects, check that all the relevant data is collected first time round – consider the overall Geometallurgy process and engage the multi-disciplinary team at the planning stage to get maximum value out of the data collection process and to make sure integral key data is collected from day one.
The third and final part of this series, available in the next edition of AMC’s Digging Deeper, will consider further how the Geometallurgy approach can be used to explore other opportunities to value add to a project or mining operation and how AMC can help you achieve this outcome.
Principal Mining Engineer
General Manager, Brisbane / Principal Consultant
Corporate Consulting Manager / Principal Geologist