Smarter Mineral Exploration with Big Data and AI IBM Watson for Mining

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Provided by: IBM
Topic: Tech Industry
Format: HTML
With prices for most mined commodities strengthening over the past year, the mining industry is emerging from the downturn that lasted from 2012 to 2016. As mining’s overall prospects brighten, however, two chronic problems remain: the declining rate of new mineral discoveries and the rising cost for each new ounce or tonne of metal or mineral added to reserves. The modern era of mineral exploration was launched after World War II, and after seven decades of prospectors and geologists scouring the globe, almost all the “easy” deposits at surface have been found and mined out. As today’s mineral explorers seek out increasingly difficult deposits, they are becoming reliant on expensive deep-drilling and data-heavy surveying. The good news for miners is that the rate of improvement in information technology over the same time period has been revolutionary, and a new suite of powerful analytical tools for mineral exploration is becoming available for the first time. Big data, artificial intelligence, and the Internet of things are some of the new phrases that today’s mineral explorers are bringing into their workday vocabulary as they seek new ways to achieve accelerated exploration, discovery and production through improved accuracy in deposit-modelling capacity — ultimately leading to new revenue streams that are achieved sooner. Another benefit for miners is the fact that the oil and gas industry is already several steps ahead in experiencing the disruption of the big data revolution. Miners are able to look across at their resource-industry cousins for inspiration and examples of best practices in bringing big data into exploration applications. In the following pages, our roundtable of experts and thought leaders delve into these topics and serve up their unique insights on this emerging field.
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