The oil and gas industry is turning to AI to help cut operating costs, predict equipment failure, and increase oil and gas output. A faulty well pump at an unmanned platform in the North Sea disrupted production in early 2019 for Aker BP, a Norwegian oil company, according to an account in the Wall Street Journal. The company installed an AI program that monitors data from sensors on the pump, flagging glitches before they can cause a shutdown, stated Lars Atle Andersen, VP of operations for the firm. Now he flies in engineers to fix such problems ahead of time and prevent a shutdown, he stated. Aker BP employed a solution from SparkCognition of Austin, Texas.

Meet Spot, the first robot to get its own employee number at Norwegian oil producer Aker BP. Developed by Boston Dynamics, the robot is set to start patrolling Aker BP's oil and gas production vessel at the Skarv field in the Norwegian Sea this year, testing its ability to run inspections, detect hydrocarbon leaks, gather data and generate reports. The upshot for Aker BP, which is seeking to be a front-runner in the digitalization of the oil industry, is to make offshore operations safer and more efficient, the company said as it presented the robot at its capital markets day in Oslo on Tuesday. Aker BP will run the tests with Cognite, the software venture controlled by the oil company's main owner, Aker ASA. "These things never get tired, they have a larger ability to adapt and to gather data," Kjetel Digre, Aker BP's senior vice president for operations, said in an interview.

The oil and gas industry's technological innovation over the last 150 years is truly astonishing, which is why its lackadaisical adoption of artificial intelligence is so surprising. Geologists have figured out how to vibrate the earth and use seismic imaging to describe rocks thousands of feet below the surface. Mechanical engineers have designed tools that can steer a drill bit through a narrow band of oil for more than a mile. Likewise, petroleum engineers have collected billions of data points from hundreds of devices to design the most productive wells. But when it comes to using that data to train an artificial intelligence to generate insights, the industry is still dabbling.