Barely a day passes without hearing about new oil patch use cases for artificial intelligence (AI) and generative AI.
These technologies offer benefits like massive time savings when it comes to dealing with data, calculations, and repetitive tasks, and they are becoming more powerful and easier to use by the day.
While AI and gen AI can serve as “superchargers” to human capabilities and provide a competitive advantage for businesses, worries linger about the technology’s tendency to “hallucinate” when providing answers and whether AI will replace knowledge workers’ jobs.
Even so, those using the tech are optimistic about its potential, although they believe humans should remain involved in the workflows.
Speaking during a session focused on generative AI at the Unconventional Resources Technical Conference (URTeC) in Houston in June, Travis Clark, enterprise AI data scientist at Chevron, said the supermajor has applied AI to improve its production in the Permian Basin.
“How can AI help extract more oil for less?” he asked.
AI is helping the company enhance its shale and tight recovery in a number of ways, including improving well production and frac design, predicting potential frac hits, and optimizing chemical selection to increase recovery, he said. It has also helped the Permian drilling and completions team learn lessons in real time that can be applied to subsequent pads. For example, the team has used AI to create a sand bridging model based on data from the drilling and completion phase to predict the likelihood a well will have issues from flowback so mitigation measures could be put in place.
“We’re sitting on quite a bit of data that we need to make sure we’re taking advantage of,” Clark said.
Chevron is also taking advantage of the potential generative AI offers. Clark said that while Chevron went “all in” on Microsoft’s Copilot when that became available, one of the early generative AI efforts the company carried out was a look-back project of wells.
