During refinery maintenance, "you're putting people in dangerous situations to do work. If you can do those turnarounds faster, you're exposing yourself to less risk," said Matthew Babin, head of energy and natural resources at software company Palantir Technologies.
Gen AI can provide "context to people who are in the process of making a decision, even if it's outside their area of expertise," Babin said.
"So if I'm a reservoir engineer, I don't have to know about maintenance, but I do have to know about maintenance when I'm looking at how that resource is going to perform and what that costs my organization," Babin added.
Petroleum installations are regularly checked or taken offline for upkeep.
A Gen AI interface provides "access to a maintenance manual, so you can look at how maintenance for that piece of kit should be done," all laid out in plain English, thanks to a chatbot, McGreevy said.
Such a system could also facilitate the repair work itself, taking the guesswork out of such decisions.
For example, the technology would allow a company to use a computer model of a facility to determine if there is enough room to use a ladder or install scaffolding, McGreevey said.
McGreevy said it could also help new employees: "I think we can shorten dramatically the time it takes for people coming on board to be proficient to safely operate these facilities at scale."
Greater efficiencies linked to Gen AI also create a chance to reduce an oil facility's carbon footprint. But running the technology also requires huge amounts of electricity, mainly in data centers.
Source: AFP
