Tag Archives: Advisian Digital

Magnetite Mines up for NextOre magnetic resonance ore sorting pilot at Razorback

Having shown potential in lab-based test work to increase head grades at the Razorback project, NextOre’s magnetic resonance (MR) ore sorting technology is to now get an outing in South Australia at the high-grade iron ore development.

Razorback owner, Magnetite Mines, says it has entered into an agreement with NextOre to supply a mobile bulk ore sorting plant using a magnetic resonance (MR) sensor for a trial of the technology at the project.

The company said: “This advances our exclusive partnership with NextOre and is an important step in our journey to unlocking the potential of the Razorback project. The company is excited by the potential of the NextOre technology to enhance processing of by ‘pre-concentrating’ run of mine ore feed to increase plant head grade.”

The NextOre agreement includes a non-refundable deposit of A$100,000 ($71,418) and contemplates further, staged payments of A$700,000, Magnetite Mines says. The scope covers supply of a full-scale mobile ore sorting plant to site at Razorback for sorting magnetite ore using MR technology during the trial period for the purpose of mine feasibility analysis. The agreement includes milestone dates, with the equipment despatch from the CSIRO Lucas Heights facility, in New South Wales, expected in 2021.

Formed in 2017 by CSIRO, Advisian Digital and RFC Ambrian, NextOre supplies MR ore sorting solutions to global mining companies that applies mineral sensing technology developed by the CSIRO.

Unlike traditional ore sorting technologies that are based on X-ray or infra-red transmission, NextOre’s on-belt MR analyser ore sorting solution allows for the grade of high throughput ore to be measured at industry-leading accuracies and speeds, NextOre says. Due to the high speed of the technology, the integrative system is able to perform the analysis, computation and physical diversion of waste ores down to one second intervals allowing for fast diversion or high-resolution sorting.

As previously reported, the company entered into an exclusivity agreement with NextOre granting Magnetite Mines exclusive use of its MR ore sorting technology for any magnetite processing applications Australia-wide and all iron ore applications in the Braemar (including New South Wales) for a period of four years.

Magnetite Mines Chairman, Peter Schubert, said: “NextOre’s magnetic resonance sorting technology, developed over many years in conjunction with the CSIRO, has a rapid response time allowing unprecedented selection accuracy and speed. The result is potential for a substantial increase in the head grade of plant feed, resulting in lower unit operating costs and a significant improvement in capital efficiency.

“This technology also offers potential environmental benefits, with enhanced water efficiency and reduced tailings volumes.”

He added: “We are particularly interested in the potential of the NextOre technology to increase the grade of ore fed to the concentrator. The bulk trial of this exciting technology will contribute to the study work now underway.”

Chris Beal, CEO of NextOre said: “We are enthusiastic supporters of Magnetite Mines’ vision of unlocking the vast resources in South Australia’s Braemar region. Their disciplined approach, which leverages emerging technologies with well-established mining methodologies, is a testament to the team’s knowledge and experience in the field.

“In our collaborative planning, the Magnetite Mines methodology of carefully integrating mine and mill activities speaks strongly to the ability to generate the maximum value from bulk ore sorting solution. I am thrilled that NextOre can contribute to this transformative project and I look forward to jointly developing Australia’s reputation as a global leader in green resource extraction.”

Magnetite Mines and NextOre sign ore sorting exclusivity pact

Magnetite Mines Ltd says it has entered into an exclusivity agreement with ore sorting technology company NextOre to use its leading-edge magnetic resonance ore sorting technology for pre-concentration of magnetite and iron ore projects.

The terms of the agreement include exclusive use for any magnetite processing applications Australia-wide and all iron ore applications in the Braemar (including New South Wales) for a period of four years.

Formed in 2017 by RFC Ambrian, Advisian Digital and the CSIRO, NextOre aims to commercialise magnetic resonance ore sorting technology, an on-belt mineral sensing technology developed by the CSIRO. The technology uses a magnetic resonance analyser (MRA), a form of radio frequency spectroscopy, for the quantitative measurement of target ore minerals.

The use of the MRA allows for a high throughput, high accuracy bulk sorting application that is typically added to the front-end of a processing flow sheet to divert waste ores away before processing, according to Magnetite Mines. “This has the effect of improving mining grades by pre-concentrating the ore that will be subject to processing, whilst rejecting significant tonnages of low-grade material to tailings via a diversion method such as a chute flop gate or dead box diverter.”

The theorised result of ore sorting is a reduced volume of upgraded ore that performs better in the processing plant while reducing processing costs as nil-value material that would ordinarily be subject to downstream processing is rejected early on, according to the company.

“Unlike traditional ore sorting technologies that are based on X-ray or infra-red transmission, NextOre’s on-belt MRA ore sorting solution allows for the grade of high throughput ore to be measured at industry-leading accuracies and speeds. Due to the high speed of the technology, the integrative system is able to perform the analysis, computation and physical diversion of waste ores down to 1 second intervals allowing for fast diversion or high resolution sorting.”

Magnetite Mines Chairman, Peter Schubert, said: “We see great potential for technology to unlock a step change in competitiveness of our Razorback iron project (pictured). NextOre has completed an initial mathematical assessment based on our extensive geological data and the results are encouraging.”

Schubert said the company was moving to bulk test work to prove its application in its Razorback iron project, which has generated some 3,900 Mt of iron ore resources and has over 110 km of unexplored strike. The company believes it will be able to produce a 68.8% Fe concentrate from the project.

He added: “NextOre’s magnetic resonance sorting technology, developed over many years in conjunction with the CSIRO, has a rapid response time allowing unprecedented selection accuracy and speed.

“The result is a substantial increase in the head grade of plant feed, resulting in lower unit operating costs and a significant improvement in capital efficiency. But the application of this technology also gives environmental benefits, with enhanced water efficiency and lower tailings levels.”

Razorback already has advantages of scale, proximity to established ports, proximity to rail and shallow stripping, according to Schubert, “but the NextOre technology takes the competitiveness of the resource to another level”.

The company has initiated a desktop study of NextOre’s ore sorting solution with initial results to-date being very positive, it said.

Initial analysis of the macro-scale heterogeneity of the Razorback iron project JORC 2012 mineral resources indicates that the orebodies are suited to the application of ore sorting.

“The highly selective technology is particularly well suited to magnetite measurement and can be calibrated for several mineral types,” it said. “Further test work is envisaged in the near future in aid of refining the existing flowsheet.”

Chris Beal, CEO of NextOre, said: “The Braemar Province is really an astonishingly vast mineralogical system and represents an incredible potential for value. Owing in large part to the way nature arranged its geology, the system appears particularly well suited to the application of bulk ore sorting systems.

“In terms of reductions in water and electricity consumption, tailings dam size reductions, and overall plant efficiencies, the application of bulk ore sorting has the potential to impact developments in the region in a significant way.”

Mine sites testing out CSIRO, Mining3’s precision mining concept

CSIRO and Mining3’s wide-ranging precision mining concept looks to be gaining momentum with multiple mining companies testing out aspects of this innovative notion to reduce the footprint of future mine sites.

Among the headlines from the organisations’ latest report on this technology was its ore sorting technology, NextOre, has three trials underway at mine sites, with up to three more systems to be delivered this year.

A Chilean copper mine is testing up to 10 types of sensors, complementing other recent trials in Australia and CSIRO desktop studies. Another study found that a mining company could make the same profit as it is now, but with a 30% reduction in capital and operating costs.

In this pursuit, the mining industry can learn a lot from medical science, according to CSIRO Research Director in Precision Mining and Mining3 Research Leader, Ewan Sellers.

As the CSIRO rock mechanics specialist says, modern medicine has used technology to better understand and treat illnesses and injuries while reducing the impact on people. Sellers is now working towards creating low impact “zero entry mines”.

CSIRO explains: “Precision mining is the industry’s version of keyhole surgery. Once a deposit is discovered, precision mining aims to target the ore and extract the deposit as economically and sustainably as possible.”

CSIRO and Mining3’s shared vision is for mines of the future to be mostly underground, remotely operated by robotics, with minimal or remote offices and a very small environmental footprint. All waste would be used to make other products.

Sellers believes this vision could become a reality for most mines within 20 years, as vast mining operations that leave large scars are consigned to history.

Minerals 4D

Key to enabling precision mining is a concept CSIRO is leading called Minerals 4D.

Minerals 4D ‘intelligence’ aims to image minerals in the subsurface and predict their distribution. By integrating sensors and specialised imaging techniques tied with data analysis and machine learning, miners can better understand the orebody and quantify the rock mass at multiple scales.

Precise cutting, blasting and in-mine processing techniques can then accurately target the ore and leave the waste behind. Miners can focus on the most economic part of the deposit, reducing the need to move, crush and process massive amounts of rock, saving significant amounts of energy, water and waste.

CSIRO said: “Although information about the grade of the material and type of rock may currently be known over a block or at mine scale, Minerals 4D aims to add information about the mineralogy at a much smaller scale. This will enable companies to target the orebody and characterise the rock mass more accurately to increase efficiency at the processing plant.”

Rob Hough, the Science Director for CSIRO Mineral Resources, says Minerals 4D is about adding a time series to three-dimensional (3D) data. Essentially, it’s about tracking mineralogy over time.

The mining industry is now capable, through its geophysical sensing technology, to create extremely accurate 3D spatial models of orebodies, but 4D adds in the critical time element – tracking that mineralogy through the metal production line as if it were a barcode in a manufacturing circuit.

The concept involves linking modular mining operations to sensors – including fibre optics and systems attached to robots – to precisely characterise material in the subsurface before mining, through to a mine face, bench, conveyor, stockpile, truck, train or a ship.

Then you can measure the chemistry, mineralogy and rock structures at a range of scales, and provide unprecedented detail and volumes of data that capture ore and waste variability. Measuring the mineralogy is critical to understanding the quality, so where the value is created and lost.

This is like the artificial intelligence algorithms that companies such as Petra Data Science are developing to track ore from the pit to the processing plant.

A focus on value, rather than volume, means less waste and emissions in this context.

“If you have the knowledge of what you’re dealing with in a 3D picture you can then start to make predictions as to how minerals will perform when you go to mine, through to process and beneficiation,” Hough says.

“Operators can choose one set of mining or processing systems over another, knowing the texture and hardness of a material. We need to understand what is in the rock mass in terms of the minerals, but also how hard it is, its strength and how it breaks up to best separate the ore from the waste rock.”

Drone-deployed sensors

It is now possible to produce a detailed face map of a mine, fly a drone with spectral sensors to image surface mineralogy and use data analytics to identify correlations between ore types and rock strength. X-ray diffraction is also being used for analysis. These instruments are applied to samples in the field, drill holes and at bespoke laboratories that run thousands of samples at a low cost in order to build a 3D mineralogy model.

“We have a range of sensors available, but we don’t yet have a fully ‘sensed’ mine,” Hough adds.

“What we’re missing is all sensors in place, in a given operation. We’re also missing the assembling of data to inform decision making throughout the process as it happens – we need that information conveyed in real time and viewed in our remote operations centres.”

Advanced sensor-based ore-sorting

CSIRO partnered with RFC Ambrian and Advisian Digital to launch joint venture, NextOre, to deliver a sensor that intelligently directs a conveyor – sorting valuable ore from waste. CSIRO said NextOre has three trials of the sensor system underway at mine sites, with up to three more systems to be delivered this year.

“On the back of better data, we should be able to take advantage of applied mathematics that will then allow us to move to artificial intelligence and machine learning,” Hough says. “I can see a real-time conveyor belt start making automatic decisions about what is coming down the line. It’s the ultimate sensing and sorting solution.”

Reducing energy and water use

Sellers believes a move to precision mining can improve the conditions for communities living nearby mines, and even improve the social acceptance of mining.

He said several companies are testing out the value cases of sensors and data integration, and he understands they need to see proof that precision mining works on the ground. The economic benefits of sensing were demonstrated recently at a Western Australia iron ore mine, where A$25 million ($17 million) of additional resources were discovered using data provided by a relatively inexpensive hyperspectral sensor, according to CSIRO.

A Chilean copper mine is testing up to 10 types of sensors, complementing other recent trials in Australia and CSIRO desktop studies, it said. Another study found a mining company could make the same profit as it is now, but with a 30% reduction in capital and operating costs.

“Once miners gain confidence that we can actually do this, I think it will take off very quickly,” he says.

Precision mineral exploration and discovery

Beyond the mine itself, tracking minerals over time – in 4D – will also benefit greenfields exploration upstream.

According to CSIRO Digital Expert, Ryan Fraser, implementing the Minerals 4D concept is at its most challenging at the exploration and discovery stage – the point where data are sparse, and little is known about a potential target orebody.

“For example, we know a lot about a deposit such as Mount Isa, including how it forms. So, can we use the intelligence we have of that mineral system to foresee where the next Mount Isa will be?” he asks.

Fraser says if we understand how mineralogy evolves over time and the overall geological process, we can then look for signatures across the Australian landscape that help to identify similar things.

“Normally you drill in these spots, take back samples, check data and then in about two years you might have some idea of what’s under the surface and have some idea of mineral boundaries.”

The new sampling techniques will be far quicker and more efficient, he says.

“Instead of sampling a sparse, evenly spaced grid, we use machine learning to reduce uncertainties and guide where to sample and that will enable us to do much smarter edge detection of mineral boundaries,” Fraser explains.

Already this kind of predictive work has been tested in a project for the South Australian (SA) government at Coompana in SA with surprisingly accurate results and significant cost savings over traditional methods, according to CSIRO.

Other key challenges that researchers and the industry are working to address to make this a reality, include designing and developing sensors robust enough to work effectively in the mining environment (for example, in robotic cutting machines) and across rock types, and understanding which sites in the mine process are most suitable for sensors.

CSIRO concluded: “These sensors will be linked to precise and automated drilling, cutting and blasting technologies under development through Mining3 to transform the way that mining is performed.”