Artificial intelligence is everywhere.
It is in your phones, the video games you play, your search engines, and everywhere else in the digital world, in one way or another.
The oil and gas industry is no different. DNV, an independent expert in assurance and risk management that provides certification and technical advisory services to the energy industry, said nearly half of the oil and gas companies it surveyed in 2024, would use AI in their operations.
Market research company Mordor Intelligence estimated global demand for AI applications in oil and gas value chains would go from US$3 billion in 2024 to US$5.2 billion in 2029.
Among the many topics looked at during the February 10-12 energy conference, Hyatt Regency, Port of Spain, experts considered the possibilities for AI in the industry. Dr Jose Celaya, principal scientist and manager of Intelligence Systems Lab presented on the ways to optimise performance in the operating systems of the oil and gas sector, making it more efficient.
CEO of the Center for Energy Resources and Digitalisation Technologies (CERDiT) Stanley Rich Wharton said it could mean even more than that to the industry. With TT being a 100-year-old oil and gas province seeking to optimise its resources, looking deeper into its borders and beyond for deepwater oil and gas, AI can open the doors to greater exploration, better processes and safer operations.
[caption id="attachment_1139862" align="alignnone" width="742"] Shuan Rampersad, CEO, Ramps Logistics. - File photo by Angelo Marcelle[/caption]
Celaya showed a video in which an AI assistant, with an understanding of the oil and gas sector, is asked to find wells in a particular region.
In the video, the user asked about data available in a certain field. The digital assistant brought up a map with a few wells and records of a well bore, as well as legal agreements, well logs and a few markers.
The user asked the assistant to pull some of the data from one report and cross-reference it with the map.
“Look at those datasets,” he said, pointing to the screen. “And now, it's doing some geologist stuff that I don’t understand.”
The assistant finally did an interpretation of the wells in the area based on the questions asked by the user and the data it had access to.
"Now, this system is not a computer, this is an energy large language model (LLM) system that we have. This system understands the domain, understands if you say well, it's not about ‘feeling well,’ it's actually ‘well,'" Celaya said.
“It understands the kind of data that we use in the reports that we use, it is contextualised with the main data, and it is connected to a data ecosystem.”
Celaya said AI systems have the ability to optimise several aspects of the oil and gas sector, but the sector can also benefit from their ability to apply knowledge, run algorithms and do high-speed computing.
“We use the domain knowledge and create a model that has a good approximation to compute benefits.”
He added that in the case of logistics, processing and m
