While outsiders may view mining like the old ‘dinosaurs’ trotting in modern industry, the truth is that miners are actually leaders in the integration of new ideas and technologies. is.
With miners operating around the world for thousands of years, it’s no wonder that much of the “easy-to-get fruit” has already been mined, especially in countries with mineral promise.
However, as has always been the case, miners have used new technologies to improve their success rates in discovering and mining the earth’s resources.
Long ago, miners evolved from using sticks to metal-based tools when searching for minerals.
Need for new technology in mineral discovery
Apart from heading into new and unexplored territory, using new technology remains one of the best ways to make big discoveries.
Universities, governments, technology development companies and mining giants are constantly researching new ideas to help explorers pinpoint commercial mineral bodies.
Thanks to increasing computing power, improved analytical techniques, and the introduction of ideas and techniques from other industries, explorers continue to uncover major new discoveries.
Two emerging technologies of growing interest in mineral exploration are artificial intelligence (AI) and a subset of AI, machine learning.
Research paper results
A newly published paper, “Predicting New Mineral Occurrences and Planetary Analogue Environments by Mineral Association Analysis,” highlights the great potential of using AI and machine learning to discover important new mineral resources.
This paper suggests that AI and machine learning may play a key role in better understanding and interpreting the large and growing mineral data resources amassed by couples. .
The authors show that, combined with the multidimensional analytical capabilities of machine learning, miners and their consultants can better understand known associations between mineral group species and distinctive geological environments to discover new minerals. suggest that this could facilitate new data-driven strategies for mineral discovery. deposits.
“Furthermore, these prediction-related methods have the potential to elucidate the origin of minerals in the context of their tectonic, environmental and possibly microbiological environments. It is an insight that highlights the
A highlight of the research results is the creation of a machine learning model using a large mineral evolutionary database consisting of 295,583 mineral localities of 5,478 mineral species, to predict the occurrence of previously unknown minerals and related rules. predicted based on
In particular, their model helped identify promising regions containing numerous important battery minerals and rare earth elements.
The team involved in this study was led by representatives from the Earth and Planetary Institute, the Carnegie Institute of Science, the University of Arizona School of Earth Sciences, the School of Chemistry and Biochemistry, the University of Notre Dame, Mindat, and Rensselaer Polytechnic Institute (RPI). , is just one of many industry and scientific bodies looking at the benefits that AI and machine learning can offer.
Bill Gates, AI, BHP
In 2021, Bill Gates and Jeff Bezos’ Silicon Valley-based start-up KoBold Metals will be the world’s largest mining company to use its technology to locate battery metal deposits. announced a partnership with the BHP Group (ASX: BHP).
The partnership was established to focus on over 193,000 square miles of Western Australia.
The search targeted copper and nickel deposits believed to be buried between 650 and 5,000 feet below the surface.
Tiban and Earth AI
Recently, Australian key minerals specialist Tivan(ASX:TVN) partnered with EARTH AI to investigate the Northern Territory’s Sandover lithium project.
EARTH AI will provide a dedicated geology team, proprietary cloud computing, and integrated geology AI review and machine learning processes to support Tiban’s work on the sandover project, which covers approximately 8,000 square kilometers.
The area is believed to contain lithium-bearing pegmatite and sediment-inlaid copper and iron copper oxide gold (IOCG) deposits identified by the Northern Territory Geological Survey.
AI offers many new opportunities
AI and machine learning will inevitably have a major impact on the mining sector, according to AI World School, a global artificial intelligence expert.
The mineral exploration industry has already been greatly impacted by this technology, and companies are adopting it to increase exploration efficiency and success rates.
The mineral exploration portion of the business sees AI with the ability to map geographic locations from multiple inputs to aid mineral exploration. Geologists also use machine learning algorithms to find ores.
AI World also points out that AI is capable of processing millions of data points and can learn from past data to help identify new targets and predict potential mineral beds in the crust. are doing.
Drones combine with AI technology to collect, process, and inspect aerial data.
The oil and gas industry will also benefit
According to GlobalData, a leading international research firm, machine learning has the potential to transform the oil and gas industry as well.
GlobalData says it can be used to analyze seismic data, well logs and other geological data to elucidate potential oil and gas reservoirs.
Machine learning algorithms can also analyze production data and identify patterns that can be used to improve well performance.
GlobalData oil and gas analyst Ravindra Puranik said machine learning as a whole has the potential to improve efficiency, increase production and reduce costs in the oil and gas industry.
The Organization for Economic Co-operation and Development (OECD) estimates that AI could add up to $16 trillion to global GDP by 2030. This equates to over 10% of his gross world product.
Around the world, resource companies are increasingly deploying AI technology to improve the odds of successful exploration.
