Organizations in the oil and gas industry are increasing their adoption of machine learning and artificial intelligence to innovate and address a wide range of use cases, from emissions monitoring to optimization of the production.
That’s what Hussein Shel, director, chief technologist and head of Upstream Energy and Utilities at Amazon Web Services (AWS), which describes itself as the world’s most comprehensive and widely adopted cloud, told Rigzone when was asked if there was any new AI. innovations in the works that could affect the oil and gas sector.
Shel added that AWS is working with companies across the industry to accelerate machine learning and AI innovation “by providing a combination of high-performance, cost-effective and energy-efficient machine learning tools and accelerators optimized for applications of machine learning.”.
In a statement sent to Rigzone, Shel offered some recent examples of how AWS customers are leveraging machine learning and AI for their business. The AWS director pointed to an agreement announced in February this year, in which Baker Hughes signed a strategic partnership agreement with AWS to develop, market and sell Leucipa’s cloud-based automated field production solution .
The collaboration leverages AWS services such as advanced analytics and Baker Hughes’ expertise in the oil and gas industry to create an automated field production solution designed to enable operators to manage field production , Baker Hughes said in a company statement at the time.
Shel also highlighted a pairing of AWS with CNX Resources Corporation and Orbital Sidekick. In a summary posted on its website, AWS noted that natural gas company CNX reduced its greenhouse gas emissions by 48 percent and increased production from its natural gas wells by four percent. cent thanks to a collaboration with AWS partner Ambyint. AWS noted on its site that Orbital Sidekick used AWS to monitor energy pipelines and reduce risks and emissions.
The AWS director also noted an AWS collaboration with Scepter and ExxonMobil, as well as a collaboration with Cepsa.
In a statement released in May, Scepter revealed that it and ExxonMobil were working with AWS to develop a data analytics platform to characterize and quantify methane emissions, initially in the U.S. Permian Basin, from multiple oil rigs. monitoring that operate from the ground, in the air and from space.
In a statement published on its site, Cepsa points out that it was one of the first companies in the world to use “in our facilities the innovative solution Amazon Lookout for Equipment, from AWS”. This technology uses machine learning models developed by AWS to help companies perform large-scale predictive maintenance on industrial facilities, Cepsa says on its site.
When Rigzone asked Vicki Knott, CEO of CruxOCM, which describes itself as the future of autonomous control room operations, if there are new AI innovations in the works that could impact the oil and gas industry, Knott offered his insight on interesting applications for large language models in industry.
“An interesting application for large language models in oil and gas will be the day when we can ask a ChatGPT-like interface for an indication like ‘can you pull the historical flows for all transmitters [asset name]clean up all the stale data and give me the average flow for 2022, or “you can pull out all the construction P&IDs and highlight to me where the MOVs are,” Knott said.
“We’re a long way from that, of course, but advances in large language models have the ability to make our industry more intuitive, which will increase the efficiency of our operations,” Knott added.
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