Data & Analytics
Schneider Electric says the deal advances its vision of creating intelligent industrial ecosystems that connect physical assets with digital insights across the asset life cycle.
With the latest addition, the Italian major’s computational capacity passes the exaflop threshold, making the firm the world’s leading company by computing power in the new TOP500 global ranking.
This work describes a study in which distributed data parallel training, paired with a node-local caching pipeline, enabled efficient multigraphics-processing-unit scaling for a CO₂-storage graph-neural-network surrogate while maintaining generalization.
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To predict liquid-loading tendencies and to identify opportunities for production enhancement, the performance of 150 gas wells was analyzed in two gas fields in India. -
Major differences exist between engineering- and nonengineering-related problems. This fact results in major differences between engineering and nonengineering applications of artificial intelligence and machine learning.
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Digital twins are powerful combinations of models and data that “age” throughout the lifecycle of an asset as they gather and integrate data from the field. This technology is a quantum leap from earlier efforts at modeling complex systems.
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This article outlines 10 top trending technologies for 2019, a list that covers diverse topics such as security, the Internet of things, reinforcement learning, energy sustainability, and smart cities.
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Joelle Pineau, a machine-learning scientist at McGill University, is leading an effort to encourage artificial-intelligence researchers to open up their code.
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The international major is calling its latest multiwell project in the Permian Basin a “beacon of innovation.” The goal is to see if combining digital technologies will lower the operating costs of its shale assets.
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As companies look to reduce the time it takes to inspect a subsea pipeline, as well as the costs involved in the operation, autonomous systems have become a more desirable option. How close are they to becoming the norm?
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Innovating internal systems at Exxon inspires executives to create a forum for the oil and gas industry.
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Should that outside hotshot lead your digital transformation work or an insider who knows more about the culture and customers?
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This paper investigates the most important independent variables, including petrophysics and completion parameters, to estimate ultimate recovery with a machine-learning algorithm. A novel machine-learning model based on random forest regression is introduced to predict estimated ultimate recovery.
