NEWS

The oil field’s digital transformation is bringing sweeping change to the upstream industry, from using data analysis to help companies find the oil, to the possibility of operating equipment autonomously.

These technological inventions will bring significant structural changes—similar to how those wrought by the advent of horizontal drilling and hydraulic fracturing changed the industry, reducing the cost of production in North America drastically.

“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,” said Thomas Halsey, chief computational scientist, Exxon Mobil, during a panel discussion on big data analytics at OTC 2017.  Halsey made the statement in response to a question asked of the panel. The question was whether digital technologies, like data analytics and machine learning, could potentially help E&P companies produce from reservoirs that weren’t previously viable—similar to how unconventional technology has opened up shale plays. Halsey said he does not see the digital oil field opening up new geologies, but he does predict that the digitalization of oilfield equipment and operations will continue for the foreseeable future, due to future competitive advantages and untold economic value.

World Oil documented similar sentiment on the topic of digital transformation from E&P CEOs in a recent survey completed by PricewaterhouseCoopers, which documented responses from a total of 1,400 CEOs in a variety of industries, from 39 countries. “To reshape the industry, chief executives stress that technological innovation, combined with digital transformation, are the principal drivers required to capitalize on new opportunities,” Craig Fleming, World Oil’s Technical Editor, wrote in his March 2017 column, The last barrel.

While most observers agree that digital technologies will bring value to the oil industry, quantifying such value remains elusive, said Halsey, because while there has been progress, it has been slow. Common barriers that have slowed progression include the upstream industry’s conservative inclination toward adopting new technology; poor data quality, due to poor data management systems and assets that have changed ownership; and cultural gaps between engineers and data scientists. “You also have to have a clear business problem (to solve),” he said, to demonstrate clear value to operators that might be potential customers for a new technology.

“There is no set pro forma of how you determine the value, so I think that if we really want to make progress as an industry, and understand where the value is, we have to be a little bit less puffy—a little bit more rigorous about finding the baseline,” Halsey said. “I’ve got manufacturing, drilling, geology—so who pays for data analytics and who makes money at it? Let’s say, for discussion purposes, that data analytics has now gotten to the point where it is in systematic use…  [The answer] is that the marketplace decides and makes the right decision.”