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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In this study, the authors investigated a fully data-driven approach using artificial neural networks (ANNs) for real-time virtual flowmetering and back-allocation in production wells. -
The authors detail the development of a technique based on surface-to-borehole controlled-source electromagnetics (CSEM), which exploits the large contrast in resistivity between injected water and oil to derive 3D resistivity distributions, proportional to saturations, in the reservoir.
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This paper discusses a project with the objective of leveraging prestack and poststack seismic data in order to reconstruct 3D images of thin, discontinuous, oil-filled packstone pay facies of the Upper and Lower Wolfcamp formation.
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In this paper, the authors describe a project to design, field trial, and qualify an alternative solution for real-time monitoring of the oil rim in carbonate reservoirs that overcomes these disadvantages.
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This industry is one often considered reactive and overly tradition-bound. These new technologies, however—and, more importantly, the drive of these researchers to harness their capabilities—prove that petroleum engineers remain at the forefront of innovation and discovery.
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While the visual element is key, the core strategic component of data visualization is the ability to unlock the story in the data.
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Instinctively, we feel that greater accuracy is better and all else should be subjected to this overriding goal. This is not so. While there are a few tasks for which a change in the second decimal place in accuracy might actually matter, for most tasks, this improvement will be irrelevant.
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The ecosystem in which an algorithm must live in order to deliver value must be viewed as a whole. The algorithm can be viewed like a car’s engine. It’s rather important, but it’s not a car yet.
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Digitalization leads oil and gas research and development investment priorities, according to DNV’s 2019 annual outlook.
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Neural networks can be as unpredictable as they are powerful. Now mathematicians are beginning to reveal how a neural network’s form will influence its function.
