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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A survey of oil and gas decision-makers by Ernst & Young sheds light on how companies are formulating their digital strategies. -
Royal Dutch Shell is heavily investing in research and development of artificial intelligence, which it hopes will provide solutions to some of its most pressing challenges.
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Blockchain technology may have gotten its start by keeping cryptocurrency traders honest, but its usefulness is expanding. And the oil and gas industry is taking advantage.
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To test your knowledge, answer these 10 questions from Jim Crompton, who teaches petroleum data analytics at the Colorado School of Mines.
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Digital solutions that have made their mark in other industries may foster stronger collaborative environments in various sectors within energy, including equipment maintenance and data management.
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Oil companies are talking big about using data and analytics, but the experts in the field are not sure what their role will be. Birol Dindoruk, SPE's technical director for management and information, talks about ensuring that they have a say.
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A new geostatistics modeling methodology that connects geostatistics and machine-learning methodologies, uses nonlinear topological mapping to reduce the original high-dimensional data space, and uses unsupervised-learning algorithms to bypass problems with supervised-learning algorithms.
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Artificial intelligence has come to the oil patch, accelerating a technical change that is transforming the conditions for the oil and gas industry’s 150,000 US workers.
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Expectations from data analytics in the upstream sector continue to evolve. Although the number and diversity of applications continue to increase, the adoption at the assetwide level faces well-known barriers and challenges.
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When you think of “data science” and “machine learning,” do the two terms blur together? This article will clarify some important and often-overlooked distinctions between the two to help better focus learning and hiring.
