intelligence test

aArtificial intelligence (AI) and machine learning have helped accelerate processes and improve efficiency in industries ranging from pharmaceuticals to finance to manufacturing.

Naturally, mineral exploration is driven by the use of technology that performs thousands of calculations to understand geological formations and determine locations for drilling and exploration, as well as to analyze the results of drilling programs for future development.

According to Jean-Philippe Payman, chief technology officer at VRIFY, which develops exploration intelligence software, AI modeling can fundamentally change what this long-term process looks like in the field.

He highlighted the technology’s data-driven approach to identifying mineral deposits more quickly. “It doesn’t just rely on interpretation or prejudice.” [when using AI]And we’re leveraging more data,” he said, noting that there can be errors and blind spots when human experts review data.

“This technology allows us to see more data in a very short period of time, in hours rather than months.”

Grant Sanden, CEO and founder of GeologicAI, sees AI as a way to change drilling programs based on new data and get better results. “Now we can say, ‘If you get this result on this hole, redesign the next hole.’” With real-time responses, you can accomplish even more, he said.

GeologicAI takes a slightly different approach when determining drill holes using AI, scanning the rock of prospective land parcels at high resolution to determine mineralization potential.

For Danny Donahue, head of growth at TerraAI, the value of AI in mineral exploration lies in reducing uncertainty.

“Multiple simulations can be done [of potential decisions] “Using many geological models, we can quantify and reduce uncertainty and optimize decision-making across many important parameters in exploration and development,” he said.

Improving the odds and minimizing costs can change the way investors look at mineral exploration, Donahue said. “As we and our partners get better at quantifying risk and the software improves, the industry will become more investable,” he added.

For Greg Tully, vice president of products at VerAI Discoveries, the power of AI technology means that deposits hidden in ground cover will eventually be revealed. “Across mineral jurisdictions, there is a lot of covered terrain that challenges traditional exploration methods,” he said.

VerAI is focused on using AI technology to uncover accessible mineral deposits across the Americas. “In favorable mining jurisdictions, that’s where most of the opportunities are,” he says.

He pointed out that in Chile, much of the land in mineral-rich areas is covered in gravel and has not been adequately explored. While standard geotechnical techniques are not adept at identifying these hidden mineral deposits, AI can help mineral explorers better understand the subsurface mineralization in these areas, he said.

Industry experts have long said that the world’s mineral resources are in decline, but Tully believes these estimates do not include the number of potential resources beneath the extensive gravel cover. “There are many protected mineral deposits waiting to be discovered,” he says.

actually

Gold miner Cartier Resources has successfully applied AI technology to advance its Cadillac gold project in Val-d’Or, Quebec. In collaboration with VRIFY, Cartier Resources needed to determine the mineralization level of the newly acquired land.

“We have had 90 years of exploration work owned by 10 exploration companies,” said Philippe Cloutier, CEO of Cartier Resources. Once Cartier acquired the land, it had to sift through the vast amount of exploration data it had collected over the years.

“Basically what AI does is [is] All the data is accumulated and you can get from point A to point B much faster,” says Cloutier.

VRIFY’s predictive modeling AI software DORA will identify many targets the company would have generated on its own, Cloutier noted.

“But we have gone one step further,” he added. “In fact, it identified areas that we could never reach. It recognized the fact that: [they] There was a direct signature or association to the money. ”

The advantage of this technique is that it can link positive signatures indicative of gold resources between cells hundreds of kilometers apart. “This is essentially Tinder dating across drill holes and data sets,” Cloutier said.

“AI is a disruptive innovation that will literally transform industries. AI can change the way data is collected, increasing discovery success rates and improving decision-making for future feasibility studies.”

Potential limitations

But explorers still need to do a significant amount of work to optimize the benefits from AI, Cloutier said.

Exploration geologists will need to test targets generated by AI and re-enter that data into datasets so the technology can learn from mistakes and failures.

He also pointed out that the data must be reliable. Unless datasets are reliable and well-edited, explorers will not be able to use AI in an understandable manner.

For AI to work effectively, data sets need to be available, he added. The technology “works much better for clients like us, where we have a wealth of data to calibrate and backpedal and say, ‘Is this correct?'” Cloutier said. “We need full cooperation and transparency. [for AI to produce the best results]”

VRIFY’s Payement also believes the lack of a centralized database is another limitation of using current technology.

“If you are not aggregating different datasets, [mining] “When you combine corporate and public sources into one database, it’s difficult to train large, general models,” he said.

But VerAI’s Tully feels more optimistic about this. “Mining jurisdictions in the Americas have invested heavily in acquiring and publishing exceptional data. [on potential exploration sites]“This is a huge opportunity for machine learning,” he said.

Another limitation is the understanding of geological data. Although AI systems can complete complex calculations at scale, the technology is not very good at understanding the geological meaning of some data.

“Exploration drilling can be expensive in some locations,” said Paul Gordon, technical director of mining advisory at SLR Consulting. “If you don’t have the right people with the right experience to check what the AI ​​is doing while you’re working, it can be a waste of time and money. The best service providers do that.”

pace of change

The adoption of AI-based technology across the mining industry is expected to be slow, leaving some dissatisfied.

“The pace of innovation in the mining industry is a key challenge,” says GeologicAI’s Sanden. “I think that’s the case [for AI] It’s so obvious that those who don’t do it will run into problems, because it’s a very structural advantage. ”

VRIFY’s Paiement said those looking to adopt AI can only realize its full value by first gaining a basic understanding of how the technology works.

“Many geologists are still getting used to predictive modeling, and only once a baseline understanding is gained can predictive solutions add real value,” he said. “If we don’t have time to create this familiarity, we risk stagnation in adoption. But fortunately, most tools like ours are intuitive and built by experts who understand the science.”

Mr. Payment noted that while disruptive technologies won’t instantly transform an industry, they can spark meaningful change.

“[AI] It brings a level of objective insight that helps you understand the value of your project. “Being able to see what’s good and what’s not good is powerful. The industry is in the early stages of embracing this type of technology-backed decision-making, especially when many companies operate on a single asset,” he said. However, we are seeing traction and recognize this is an important step towards more confident and transparent exploration. ”

SLR’s Gordon said there need to be some big success stories for AI to be more widely taken up by the industry.

“Until the industry starts seeing consistent results, it’s not going to be widely adopted,” he says. “But potentially [AI] Once a tipping point is reached, adoption will be more rapid. ”

Even if the adoption of AI technology becomes more widespread, Gordon believes it will have a minimal impact on the global mineral exploration landscape. “There is no silver bullet in mineral exploration, especially as you get lower in grade,” he says.

He pointed out that there are other structural limitations to adopting this technology. Major companies have been cutting back on greenfield exploration over the past decade, but there is a shortage of experts who can provide the necessary background for AI discoveries.

“I don’t think it will bring about another golden age of exploration,” Gordon said. The biggest impact AI could have is limiting exploration costs through increased efficiency, he added. “However, the amount of data we have to work with can be overwhelming, so there is no doubt that AI can help us see things that were previously invisible.”

Cartier Resources’ Cloutier said explorers still need to consider real-world constraints when using the technology, including regulations and the possibility of securing a social license to operate.

“We have to see if we can mine it,” he said. “If you can’t mine it, why bother trying to find it?”

But for now, there is widespread optimism about the role AI can play in improving mineral exploration, especially among service providers.

“We’ve just scratched the surface,” Payment said. “There are many things you can do.”