AI/machine learning
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.
Reaching further than dashboards and data lakes, the agentic oil field envisions artificial intelligence systems that reason, act, and optimize.
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Gautam Swami, manager of corporate R&D at NOV and SPE member, shares his experiences in building a career in oil and gas R&D, discusses how innovation is shaping the industry, and offers guidance to young professionals. -
Aramco’s latest MOUs focus on driving innovation and growth across oil, gas, and downstream sectors.
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This article presents a comparative study evaluating four machine-learning approaches, including three deep-learning methods, for forecasting gas and condensate production over a 5-year horizon.
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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 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.
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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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The full potential of data can only be realized when it is viewed not in isolation but as part of the dynamic triad of hydrocarbons, the data, and the people who interpret it and act on it.
