The Digital Future of E&P Can Lead to Data-Driven Anxiety

Abstract

The constant talk about the data-driven future of the oil and gas business poses a threatening question for some petroleum engineers: What do I need to know to ensure I have a job next year? Many universities are adding digital data and analytics programs to prepare petroleum engineering students, many of whom are also taking the initiative on their own to master the tools used for this new way of working in the industry. Jim Crompton, an adjunct faculty member at the Colorado School of Mines who created and taught some of the first such classes, said students who grew up in the Internet era pick it up quickly. He said he worries, though, about working engineers. “The greater challenge is for those with 10–20 years of experience,” he said, specifically engineers who do not know programming and do not have the vocabulary of digital analysis. Engineers who survived the mass layoffs of the last downturn are likely to be suffering from digital anxiety, he said. Some have seen warning signs. “They didn’t get the job they wanted or a promotion or something like that,” Crompton said. A major hurdle for many of those engineers is that their demanding jobs leave little time for training. Managers are more likely than others to be unaware of the need to know digital-data concepts, Crompton said. Decision makers also need to understand digital-analysis methods well enough to get a feel for whether the analysis is legitimate. Failure to detect flawed analysis when approving projects can “waste a bunch of money,” Crompton said. As digital-data programs proliferate, SPE is developing an online training program and is working on curriculum guidelines for data science and digital engineering in petroleum engineering schools. Birol Dindoruk, SPE’s technical director for management and information, who has made data-related issues a priority, said he expects to submit the guidelines to the SPE Board of Directors this year. Need To Know Making the case for knowing about digital data is relatively easy, but figuring out what a petroleum engineer needs to know can be complicated. The amalgam of petroleum engineering, data science, and information technology has so many elements that finding a short label for it is difficult. Requirements also vary on the basis of job descriptions. One thing is clear: Collaboration skills are required. Companies with data scientists, often from outside the oil business, tend to pair them with an engineer. The range of knowledge those two possess exceeds what each is expected to have, Crompton said. Engineers managing assets will need to have a working knowledge of the tools and vocabulary used to collaborate with data engineers, and a strong base of traditional engineering concepts is needed because advanced data analysis can generate multiple answers, some of which are unhelpful. “When it is wrong, it can miss by a mile,” Crompton said. Artificial intelligence is “a bit of a leap forward into the unknown,” he added. A person with a firm grasp of the physics of oil and gas exploration and production is required to help identify the good and bad ideas.