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Home In Depth Management

The value of resource optimisation

by Maria Highland
August 22, 2022
in Case Studies, Features, Management, Other
Reading Time: 5 mins read
A A
Eltirus discusses how to get the most out of your quarry operations using resource optimisation solutions.

Stone quarry from above. Extraction of sand and stone in a huge quarry. View from a great height, beautiful rocks in a deep quarry

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Eltirus principal mining engineer Greg Lister and Eltirus technical services manager Jackie Gauntlett discuss how to get the most out of quarry operations using resource optimisation solutions.

Brisbane-based consultancy Eltirus focuses on digital transformation and sustainable solutions for quarries. It has found that applying best practice mining industry resource optimisation solutions to quarrying has resulted in revolutionary results for clients.

To date, the quarrying industry has rarely utilised resource optimisation, despite it adding value to the mining industry for several decades. Resource optimisation considers the geological, financial, and operating constraints for an extractive operation and algorithmically determines the optimal pit that should be extracted.

Anything outside of that optimal pit is determined as being uneconomic to extract, given the assumptions used.

“Historically, in quarrying, decisions on where to extract and how to stage the extraction are undertaken using rules of thumb or simplistic calculations – like overburden thickness contours,” Eltirus technical services manager Jackie Gauntlett explained.

“These methods often neglect the key geological, geotechnical, and economic aspects of a quarry, which can result in significant loss of realised value.”

Changing course with resource optimisation
Essentially, the process of resource optimisation is to determine the optimal extraction boundary and extraction sequence for a particular deposit with the intent to maximise value.

In technical terms, optimisation seeks to maximise net present value (NPV) or cumulative discounted cash flow (DCF) for an extractive operation. The result of each optimisation scenario is the algorithmic selection of the optimal resource blocks to be extracted across the life of the scenario, the order of block extraction, and the NPV generated by the scenario.

A recent project led by Eltirus saw a 42 per cent improvement in potential NPV after optimisation.

The client, a company that trades in aggregate products, wanted to know the best approach to expand an existing operation. Eltirus undertook scenario testing using Deswik Global Optimisation (Deswik.GO), to execute and analyse the resource optimisation.

“We worked with our client to determine realistic scenario assumptions and utilised Deswik.GO to determine the projected financial outcomes with and without optimisation.

We were able to achieve a 42 per cent improvement in NPV over 30 years,” Eltirus principal mining engineer Greg Lister said.

Software evolution optimises the ultimate pit
“The key benefit of using Deswik.GO is not only being able to give clients the ‘optimal pit’, but most importantly, being able to advise them on how to stage that pit,” Lister explained.

“Deswik.GO is the latest generation of resource optimisation solutions that uses a set of innovative algorithms.

“Instead of using the previous generation of Pseudoflow or Lerchs-Grossmann algorithms made popular by Whittle, Deswik GO utilises Direct Block Scheduling (DBS), a phase generation algorithm, and a linear programming Phase Bench Scheduling (PBS) algorithm,” he said.

Optimisation results from previous generation algorithms were relatively simple with limited outputs.

Next generation software such as Deswik.GO considers the geological, geotechnical, and financial aspects of a mining operation. A major benefits is that complex constraints and assumptions can be applied to the schedule, such as ratios of material types to blend into products.

Furthermore, it allows for the semi-automated determination of phased stages, which has previously been a very manual labour intensive, time-consuming, and iterative process.

An additional benefit of resource optimisation is the ability to test a number of scenarios quickly and objectively.

An example of this is to stress test changes in sales mixes. For example, aggregate heavy versus road base heavy or to stress test changes in costs or revenues.

By understanding how the optimised extraction sequence responds to changes in input assumptions, a strategic decision can be made as to how to progress development, whilst minimising risks associated with the unknown.

Case study
A regional quarry operation in New South Wales turned to provide assistance with geological modelling and resource assessment.

The quarry produces a blend of roadbases, aggregates, and several other minor products, such as armour rock, ballast, and dust. The geology and degree of weathering is highly heterogenous making it both difficult and dangerous to plan on rules of thumb alone.

The quarry already had a long-term extraction plan in place based on a previous generation geological model, however the extraction sequence was not based on quantitative resource optimisation.

Given the high degree of heterogeneity in the distribution of geological materials, Eltirus suggested that the quarry use resource optimisation to work out the best way to stage extraction.

A set of optimisation scenarios were undertaken to investigate the impact of various assumptions regarding mining intensity, product blend ratios, sales forecasts, and extraction limits.

The goal was to determine not only the optimal pit shell and extraction sequence, but also to explore whether changing the assumptions significantly altered the optimal pit boundary or staging sequence over a 30-year period.

A recommended optimal pit and extraction sequence was thus determined after analysing various scenarios. The staged extraction sequence of this optimised scenario was significantly different to the original conceptual plan that was in place.

To evaluate the value gained from optimisation, Eltirus explored an additional scenario where extraction was in line with the original, conceptual, and non-optimised staged extraction plan. These results were compared to the optimised case.

Results
Following an unoptimised extraction schedule, the client could expect to extract 21 per cent additional waste material for the same amount of product during the first 30 years. This would result in a strip ratio increase from 0.21 to 0.26.

Most of this additional stripping is in the first six years of the schedule. As a direct result of the additional stripping at the front end of the schedule and the severe impact on cash flow during this period, there is a $3.42 million reduction in NPV.

This stems from the resultant material cash flow and cumulative discounted cashflow (i.e., the NPV) of $8.11 million for the unoptimised case, versus the NPV of $11.53 million for an optimised case, demonstrating an increase of 42 per cent.

In other studies, Eltirus has determined that for a medium-to-large aggregate quarry, CO2 emissions of approximately 2kg per extracted tonne can be expected. This includes emissions from drill and blast, load and haul, and processing.

The increased stripping requirements in the first 30 years of the unoptimised schedule would realise a 4.2 per cent increase in CO2 emissions compared to the optimised scenario.

Therefore, by integrating best practice resource optimisation into a quarry business, there is significant potential to improve the economic and social sustainability of quarries today.

For more information, visit eltirus.com

This feature first appeared in the July issue of Quarry.

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