NEWS

Exploration scientists scouring Earth’s geology for carbon-bearing minerals are endeavoring to remove the guesswork from the process, and they are doing so by deploying strategies from the playbooks of tech giants like Netflix and Amazon, according to a recent report by Reuters.

The observation, made in an article from Aug. 1, stems from a recently published study in the American Mineralogist. The study documents work accomplished with the Deep Carbon Observatory at the Carnegie Institution for Science in Washington, and is titled “Network analysis of mineralogical systems.” The exploration process used by the scientists apparently went “beyond traditional geology by amassing data about how and where minerals have formed, for instance, by the cooling of lava after volcanic eruptions.” Reuters reported that the technique has assisted the team of explorationists in discovering 10 new carbon-bearing minerals, as part of The Carbon Mineral Challenge sponsored by the Deep Carbon Observatory, but that it could also be applied to exploration for oil and gas resources.

The study’s lead author, Shaunna Morrison, who is on staff at the Deep Carbon Observatory, said that while geologists have depended on luck during past exploration operations, the new process explores for minerals “in a much more systematic way.” Moreover, Robert Hazen, executive director of the Deep Carbon Observatory, compared the new tactics to those used by Amazon to curate book recommendations based on past purchases, and by Netflix to advise viewers on new movies from historical preferences. “They are using vast amounts of data and make correlations that you could never make (without high-powered algorithms),” Hazen said to Reuters in an interview. He even compared the makeup of mineral formations to social networks, remarking that “when you see minerals together, it’s very like the way that humans interact in social networks such as Facebook.” A sign of the project’s validity is news that the U.S. Geological Survey is now partnering with the Deep Carbon Observatory, the article noted.

While several major oil companies also have large internal operations focusing on similar work, it’s interesting that nevertheless, the scientists at the Deep Carbon Observatory are modeling their efforts on accomplishments made by tech companies. There are several takeaways one could make from such a circumstance. One such conclusion is that, for all of its advancement in automation over the past decade, the E&P industry still trails Silicon Valley, with a start-up culture largely perceived as America’s bastion of innovation. A second thought is that while some companies may be stuck in their old ways, others are innovating at the same pace as Silicon Valley—only on a proprietary level.

Neither situation seems particularly optimal. While the former is a more obvious downer, the latter could indicate that the oil and gas industry is presenting a problematic image to the public. An industry hindered by a lack of tolerance—or lacking understanding—of new ideas, will find it difficult to recruit the best and brightest talent of future generations, which have been lured en masse to Silicon Valley. Such a circumstance could reinforce a trend in which the oil and gas industry is behind the tech industry indefinitely. Furthermore, if proprietary predilections keep talent from learning about the digital progress made by E&P companies, it leaves the industry in a similar predicament—lagging in recruitment and thus, lagging in quality—similar to how a poor farm system hinders a big league baseball franchise, long-term.

Yet, in the midst of the collaborative culture shaped by the current downturn, there is reason to believe that the dynamic around innovation in the oil and gas industry could be changing for the better. Companies are trying harder than ever to work together, to reduce costs and remain viable, investing in new technologies that are classified under the digital transformation umbrella. Such efforts must continue as the upstream sector continues on the road toward recovery. As ExxonMobil’s chief computational scientist put it during a panel discussion on big data analytics at OTC 2017, “I see it as a technology and a set of tools, that 20 years from now, if you don’t know how to use and deploy them, you are not going to be in business in this industry.”