INDUSTRY WATCH equipment parameters in real time and optimising pumping rates.
AI can also help prevent plant shutdowns, which can cost enormous amounts of money. Global energy giant Woodside Energy is using AI algorithms combined with thousands of sensors to detect and prevent foaming incidents at its Pluto Liquid Natural Gas plant in Western Australia. Foaming incidents require the plant to be shut down. One incident reportedly cost Woodside $ 300 million in lost revenues, so the company added an AI system that can detect the early signs of foaming up to four days in advance. A cloud IoT platform ingests data from 10,000 sensors within and around the plant’ s acid gas removal units, looking for the early signs of foaming. The system offers clear warnings of a foaming event long before it happens, meaning that the plant can adjust operations or perform planned maintenance, rather than losing revenue. Woodside now plans to expand the system to five other onshore and offshore facilities and vessels.
LLMs are also beginning to find uses in the sector. who would give it to a data scientist and get a onetime report with the results. Now that the models can write and run code, you can ask a question using conversational language – it writes the code, runs it and gives you your report immediately.
LLMs can also provide an easy way to access information such as repair manuals, offering a way to put information into technicians’ hands at drilling sites.
Companies in the oil and gas space are routinely dealing with highly private data, so they opt for private LLMs tailored to the industry, which can help streamline workflows across the organisations, allowing workers to automate reporting and democratise access to insights between business units. Customers retrain models to be very specific, to only get data from reputable sources, so they get accuracy and ultimate value.
A smarter future
Organisations that are successful with AI in the oil and gas sector are those that are focused on the tangible.
Previously a workflow might be that an oil producer would want to understand what might happen if they increased output: they would go to a business analyst
For the oil and gas sector, AI is not about technology for technology’ s sake: it is about improving efficiency, improving safety and delivering long-term value. p
62 INTELLIGENTCIO LATAM www. intelligentcio. com