Exploration serves as the backbone of the industry as it ensures the development of enough new producing mines to replenish exhausted projects. But this segment of the industry is also the most likely to suffer from budget restrictions during downturns as it is one of the most capital-intensive phases of a mine. “Although the mining industry widely accepts that exploration is important for the sector’s future, the major miners continue to allocate only a small proportion of their revenues to exploration efforts,” says S&P Global Market Intelligence in its report, World Exploration Trends, released in March 2018. “From 2012 to 2016, these [major miners] slashed exploration spending at a faster pace than their revenues declined, causing a fall in the group’s ratio of exploration spend to revenue, from 3.2 percent in 2012 to a 12-year low of 1.8 percent in 2016.”

Considering that globally, the future supply of minerals may be at risk and access to capital continues to be a challenge, it may be time for mining companies to start thinking outside of the box when it comes to its traditional exploration methods. But where to start?

“Over the last few decades, a tremendous amount of data has been collected from mining and exploration companies alike that goes completely unused,” says Denis Laviolette CEO and Director of Goldspot Discoveries in an interview with Mining Technology Partners. “When a company is hired to do remote sensing, it looks at various maps and creates a model out of the assay information. In this process it collects all kinds of data that goes to waste if it is not used on the model.”

Companies spend millions collecting information for new projects but thanks to secrecy surrounding geological data, the information is never used to its full potential. “Within the mining industry, I definitely see a lack of sharing and I see data being lost around me because there is no robust system to keep it together,” says Carrie Wong, author for Geology for Investors, a website that evaluates mineral exploration and projects for resource investors. “Every time a junior mining company goes under, information is lost. This effect is greatly magnified during recessions,” she explains. She believes that there are three main reasons behind the resistance to share information: the high costs of obtaining data, the complex approval process that companies need to make information public and the desire to maintain a competitive edge over others.

Overcoming Adversity

However, those that are pioneering in the use of multidisciplinary knowledge and new tools are benefitting from smoother and faster discoveries. In this matter, Rob McEwen’s Goldcorp Challenge may have been the first to pave the way by daring to open-source data that was traditionally kept under lock and key.

In 1989, McEwen acquired Red Lake, an underperforming gold mine that he believed had the potential to produce much more. But after seeing his team of geologists struggle to find the main gold deposit, McEwen had an epiphany during a conference on how the Linux software operating system used open-sourced data, according to Wikinomics. He decided to copy Linux’s strategy by releasing 400MB of information onto the internet by means of a contest in the hope of finding a solution for his mine through crowdsourcing.

The move was highly controversial considering that in 2000 the internet was just starting to become widespread along with the fact that, to this day, making data public is still taboo in the industry. But the risk was not in vain as the contest attracted over 1,000 contestants that competed for a prize of CA$575,000. “The contestants had identified 110 targets on the Red Lake property, 50 percent of which had not been previously identified by the company,” explains Wikinomics. “Over 80 percent of the new targets yielded substantial quantities of gold. In fact, since the challenge was initiated, an astounding 8 million ounces of gold have been found.”

The book concludes that the success of the contest validates the benefits of using non-traditional strategies to solve challenges in the industry. “Perhaps the most lasting legacy of the Goldcorp Challenge is the validation of an ingenious approach to exploration in what remains a conservative and highly secretive industry,” it says. “Rob McEwen bucked an industry trend by sharing the company’s proprietary data and simultaneously transformed two lumbering exploration processes into a modem-distributed gold discovery engine that harnessed some of the most talented minds in the field.”

Continuing the Legacy

When it comes to finding new methods for exploration and data collection, many companies are stepping up to the challenge, one of which is Earth AI. The online mineral exploration platform seeks to analyze “the input of geophysical, satellite and geochemical data, to predict the mineral composition of areas and allows users to upload their own information so that the training data pool is constantly growing,” explains Molly Lempriere, feature writer for NRI Digital and contributor in Mining Technology.

She explains that Earth AI designed the platform as a way to improve mining companies’ capabilities to predict where future deposits lie, “facilitating the comparison of formations and signatures.” And the project has attracted attention from prestigious funds. “Airtree and Blackbird Ventures, two of Australia’s biggest technology venture capital funds, are two of the most high-profile recent investors in Earth AI.”

Mexico is throwing its hat into the ring as well as companies operating in the country are incorporating these new trends into their business models. “We feel optimistic about the future given the increasing number of opportunities to analyze data within the industry,” says Alejandra Torijano, Country Manager of Agilent Technologies.

The efficient use of data may even become a make-or-break situation for mining companies as it starts to become a standard. “Once measured by how well a company extracted resources, the industry’s value proposition may be shifting to how well a company acts on information to optimize production, reduce costs, increase efficiency, and improve safety,” says Deloitte’s report, Tracking the Trends 2018. “In short, data— and the ability to organize, manage, and process it—is rapidly becoming a competitive differentiator and may even spur new business models.”


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