Hardly a day goes by that we don’t hear about new oilfield use cases for artificial intelligence (AI) and generative AI.
These technologies offer benefits such as significant time savings when it comes to processing data, computations, and repetitive tasks, and are becoming more powerful and easier to use every day.
AI and Generations AI can act as a “supercharger” of human capabilities, giving businesses a competitive advantage, but concerns persist about the technology’s tendency to “illusion” when providing answers and that it will replace the jobs of knowledge workers.
Still, those using the technology are optimistic about its potential, even as they believe humans should remain involved in the workflow.
Speaking at a session focused on generative AI at the Unconventional Resources Technical Conference (URTeC) in Houston in June, he said: travis clark Chevron’s enterprise AI data scientist said the major company applied AI to improve production in the Permian Basin.
“How can AI extract more oil for less cost?” he asked.
He said AI is helping the company enhance its shale and tight recovery in a variety of ways, including improving well production and frac design, predicting potential frac hits, and optimizing chemical selection to increase recovery. It also helped Permian’s drilling and completion teams learn lessons in real time that can be applied to subsequent pads. For example, the team used AI to create a sand bridging model based on data from the drilling and completion stages to predict potential backflow problems in the well and take mitigation measures.
“We store a lot of data that we need to make sure we use,” Clark said.
Chevron is also leveraging potential generative AI offers. Clark said Chevron was “all in” on Microsoft’s CoPilot when it became available, but one of the company’s early generative AI efforts was the well tracing project.
