AI and machine learning helping miners find new resources

While outsiders may view the mining industry as a lumbering old “dinosaur” in the modern industrial world, the truth is that miners are often leaders in the integration of new ideas and technology.

With miners operating across the globe for thousands of years, it is no wonder much of the “low hanging fruit” has already been picked, particularly in countries with the greatest mineral prospectivity.

But, as it has done through the ages with miners are using new technologies to improve their successes in finding and then mining the earth’s resources.

In the distant past, for example, that has seen miners advance from using sticks to metal-based tools in their hunt for minerals.

The need for new technologies in mineral discovery

Apart from heading to new or underexplored areas, the use of new technologies continues to be one of the best ways to make a big discovery.

Universities, governments, technology development companies and the mining majors are constantly investigating new ideas that can help explorers pinpoint commercial mineral bodies.

Thanks to ever increasing computing power, improved assaying techniques and the adaption of ideas and technologies from other industries, explorers continue to lift the cover on major new discoveries.

Two modern technologies that are obtaining increasing interest in the hunt for minerals is artificial intelligence (AI) and machine learning – a subset of AI.

Research paper findings

A newly published paper “Predicting new mineral occurrences and planetary analog environments via mineral association analysis” has highlighted the tremendous potential to uncover critical new minerals resources using AI and machine learning.

The paper suggests that AI and machine learning can play a major role in helping to better understand and interpret the large and growing mineral data resources accumulating across the couple.

The authors suggest that, coupled with the multidimensional analytical capabilities of machine learning, miners and their consultants can facilitate a new data-driven strategy for mineral discovery, through a better understanding of the known associations of mineral suites species and distinctive geological settings to uncover new mineral deposits.

“These predictive association methods, furthermore, hold the promise of elucidating mineral origins in the contexts of their tectonic, environmental, and perhaps microbiological settings—insights that highlight the co-evolving geosphere and biosphere,” the authors concur.

The highlight of the study results was the creation of a machine learning model utilising a massive mineral evolution database made up from 295,583 mineral localities of 5,478 mineral species, to predict previously unknown mineral occurrences based on association rules.

Notably, their model helped identify promising areas containing a number critical battery minerals and rare earth elements.

The team involved in the study led by representatives from the Earth and Planets Laboratory, Carnegie Institution for Science, the Department of Geosciences, University Of Arizona, the Department of Chemistry and Biochemistry, University of Notre Dame, Mindat and Rensselaer Polytechnic Institute (RPI), are just one of a number of industry and science bodies looking at the advantages AI and Machine Learning can offer.

Bill Gates, AI and BHP

In 2021, the Bill Gates and Jeff Bezos the Silicon Valley-based startup, KoBold Metals, announced a partnership with the world’s largest mining company, BHP Group (ASX: BHP), to use its technology to locate battery metal deposits.

The partnership was created to focus on a more than 193,000-square-mile area of Western Australia.

The search was targeting copper and nickel deposits believed to be buried from 650 feet to 5,000 feet below the surface.

Tivan and Earth AI

More recently, Australian critical minerals specialist Tivan (ASX: TVN) formed an alliance with EARTH AI to explore the Sandover lithium project in the Northern Territory.

EARTH AI will provide a specialist geological team, proprietary cloud computing and an integrated geological AI review and machine learning process to support Tivan’s work on the Sandover project which covers approximately 8,000 sq km.

The area is considered prospective to host the lithium-bearing pegmatites and a sediment-hosted copper and iron oxide copper gold (IOCG) deposits identified by the Northern Territory Geological Survey.

AI provides many new opportunities

According to global Artificial Intelligence specialist AI World School, AI and machine learning are inevitably going to have a huge impact in the mining sector.

It says the mineral exploration industry is already greatly influenced by the technologies, with companies implementing them to increase the efficiency and success rate of exploration.

For the mineral exploration part of the business, AI has been identified to have the capability of mapping of geographic locations from multiple inputs, assisting in mineral prospecting. Geologists also utilise machine learning algorithms to discover ores.

AI World also notes that AI is capable of processing millions of data points and learn from historical data, assisting in the identification of new targets, while predicting possible mineral beds in the Earth crust.

Drones are also being coupled with AI technology to gather aerial data, process it and inspect potential exploration sites.

Oil and gas industry also benefiting

According to leading international research firm, GlobalData, machine learning has potential to also significantly transform oil and gas industry.

GlobalData says it can be used to analyse seismic data, well logs, and other geologic data to unravel potential oil and gas reservoirs.

Machine learning algorithms are also capable of analysing production data and identifying patterns that can be used to improve well performance.

Ravindra Puranik, Oil and Gas Analyst at GlobalData, said that overall, machine learning has the potential to improve efficiency, increase production, and reduce costs in the oil and gas industry.

The Organisation for Economic Co-operation and Development (OECD) estimates that AI could add as much as US$16 trillion to the world’s GDP by 2030, equivalent to more than 10% of the gross world product.

All across the globe, resource companies are increasingly including AI technologies to help improve their odds of exploration success.