Data & Analytics
SLB's and Baker Hughes' partnerships with NVIDIA and Google Cloud, respectively, will develop advanced AI-enabled power optimization and sustainability solutions for the global data center sector.
ExxonMobil's Jason Gahr uses the five stages of grief to explain how the upstream industry should respond to the rise of AI.
This paper presents a robust workflow to identify optimization opportunities in gas lift wells through real-time data analysis and a surveillance-by-exception methodology.
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The companies completed a technical assessment of the technology for use with floating production, storage, and offloading vessels. -
The USV Challenger will be remotely controlled from shore and will be equipped with multiple autonomous features.
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After a successful trial phase of ENERGYai, AIQ has been tapped to roll out the technology across ADNOC’s upstream operations.
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Weatherford and AIQ say they aim to enable the energy sector to unlock efficiencies, boost productivity, and reduce operational costs by combining their strengths.
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This article is the second in a Q&A series from the SPE Research and Development Technical Section focusing on emerging energy technologies. In this piece, Madhava Syamlal, CEO and founder of QubitSolve, discusses the present and future of quantum computing.
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This paper describes the operator’s digital-twin end-to-end production system deployed for model-based surveillance and optimization.
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The authors of this paper describe a project to develop a virtual sensor to monitor the cooling effect downstream of a subsea choke to avoid hydrate plugs during cold-start operations.
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This paper presents an immersive platform that enables multidisciplinary teams and management to make decisions, connecting professionals to demonstrate and share findings in a way that capitalizes on artificial intelligence and cognitive capabilities.
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The paper showcases the digital journey of a brownfield where digital solutions are enhancing recoverable volume, production, and process efficiency while minimizing losses and maximizing the return of investment.
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The rapid development of oil and gas intelligent operations depends on artificial intelligence, automation, and data analytics to achieve optimal conditions in oil and gas operations.
