Abstract

Data analytics is the future of getting ahead for engineers and geoscientists in the exploration and production (E&P) business. Three executives of large companies recently played up the growing importance of data-driven employee development, from data science boot camps at BP to the Citizen Data Scientist program at ConocoPhillips. “We have got a data science community that is growing by leaps and bounds,” said Michael Rowley, director of technology and innovation at BP, during a presentation at the recent Data Science Convention 2018 put on by the Data Analytics Study Group of the SPE Gulf Coast Section. “The most powerful way for us to pro-mote data analytics is to give our technical people training so they are fully armed with data analytics tools,” said Greg Leveille, chief technology officer of ConocoPhillips. Those willing to learn and apply these new tools “will have a disproportional impact on each of your companies,” Leveille said, adding “our industry will be populated by people who know and who can do data analytics well.” In a tough job market, data skills could offer a critical edge. If two people are interviewing for a job in unconventional exploration, and one has analytics skills and experience and the other does not, “guess who gets the job,” said Andy Flowers, director of advanced analytics for Marathon Oil. One sign of the times was the number of data scientists asking questions at the gathering. Another was the 400-person crowd at the first-ever gathering. They are building and maintaining the industry’s new data gathering and analysis infrastructure, putting large databases and analytical tools in the hands of engineers, geoscientists, and financial managers. They are a small part of the E&P workforce, are hard to find, and costly to hire. “We feel like we won the lottery when we get a new person in” for the data science team, Flowers said. But engineers and geoscientists will remain central to E&P companies because “you cannot outsource knowledge of the oil industry,” Flowers said. They will be asked to use their experience to focus the work on the most important problems, and apply methods drawing on both traditional and statistical approaches. “People with a good grounding and understanding of physics, combined with analytics, can solve problems that are very hard to solve” with first principles physics, Leveille said. Increasingly, the data-driven tools will also integrate the economic aspects of decision making. Engineering decisions need to be aligned with current corporate goals. An application integrating technical and economic information could help an engineer tailor a gas project development plan based on predicted demand. “Not everything is about geology and physics,” Rowley said. Another priority is to figure out “how to connect up data in the financial space,” he said.

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