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Long before the current craze surrounding generative AI , the energy sector employed traditional artificial intelligence through its use of data to identify oil and gas deposits. In recent years the downstream industry, which includes refineries that process crude oil into gasoline, has increasingly relied on so-called digital twins — computer-modeled replicas of actual facilities.
The data-filled chatbot could allow oil field or refinery workers encountering a problem to measure atmospheric conditions like humidity and operational performance like wellhead pressure to quickly diagnose the issue, McGreevy said.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.
Such a system could also facilitate the repair work itself, taking the guesswork out of such decisions.