Organizations across 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 production optimization.
That’s what Hussein Shel, the Director, Chief Technologist, and Head of Upstream for Energy and Utilities at Amazon Web Services (AWS), which describes itself as the world’s most comprehensive and broadly adopted cloud, told Rigzone when asked if there were any new AI innovations in the works that could affect the oil and gas sector.
Shel added that AWS is working with businesses across the industry to accelerate machine learning and AI innovation “by providing a combination of high-performance, cost-effective, and energy-efficient purpose-built machine learning tools and accelerators, optimized for machine learning applications”.
In a statement sent to Rigzone, Shel offered a few recent examples of how AWS customers are levering machine learning and AI for their business. The AWS Director pointed out a deal announced back in February this year, which saw Baker Hughes sign a strategic collaboration agreement with AWS to develop, market, and sell the cloud based Leucipa 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 allow operators to manage field production, Baker Hughes noted in a company statement at the time.
Shel also highlighted an AWS pairing with CNX Resources Corporation and Orbital Sidekick. In a summary posted on its website, AWS noted that that natural gas company CNX reduced its greenhouse gas emissions by 48 percent and increased the production of its natural gas wells by four percent through 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 pointed out an AWS collaboration with Scepter and ExxonMobil, as well as a collaboration with Cepsa.
In a statement posted back 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 various monitoring platforms that operate from the ground, in the air and from space.
In a statement posted on its site, Cepsa notes 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 to perform large-scale predictive maintenance in industrial facilities, Cepsa states on its site.
When Rigzone asked Vicki Knott, the CEO of CruxOCM, which describes itself as the future of autonomous control room operations, if there any new AI innovations in the works that could affect the oil and gas sector, Knott offered her view on interesting applications for large language models in the industry.
“An interesting application for large language models in oil and gas will be the day when we can ask a ChatGPT-like interface a prompt along the lines of ‘can you pull historical flow rates for all transmitters on [asset name], clean out all stale data, and give me the average flow rate for 2022’, or ‘can you pull all of the construction P&IDs and highlight for me where the MOVs are’,” Knott said. READ THE FULL ARTICLE
