Data & Analytics
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.
This paper presents a novel reservoir engineering/reservoir simulation approach—a data-driven interwell-connectivity model augmented as a digital twin—to predict reservoir dynamics and optimize operations in the Changqing oil field of China.
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Oil and gas companies play important roles in the global push for energy security and carbon reduction. Here’s how they can excel at both. -
The complete paper describes a combination of best practices and innovative techniques that help to provide rig-based and rigless opportunities by estimating potential and risk in a naturally fractured reservoir.
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Gaining insights from digital data in the highly technical exploration and production industry requires experience, knowledge, and awareness about the acquisition of the data. The technologies presented here aim to facilitate the decision-making process while requiring less time and lower costs without sacrificing the accuracy of the data and still decreasing the prob…
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The authors of this paper describe the development and implementation of a data-streaming solution that allows for real-time processing and interpretation of fiber-optics data.
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The authors of this paper present a system, developed to achieve data transmission using a time-division approach, that includes sealed chambers for microchip storage, a power-release device, and a circuit.
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Industry leaders are harnessing the power of data to improve efficiencies, eliminate nonproductive time, and reduce Capex.
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The data-management company has raised its investment in the technology company IWS by $7.9 million, with an agreement to invest an additional $25 million depending on the performance of IWS.
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The optimization process presented in this paper gradually incorporates process control, digital twins, planning, scheduling, and blending for refiners.
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A recently signed memorandum of understanding is designed to let the two companies work together on digital transformation and decarbonization.
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Synthetic data generation is a solution that allows citizen data scientists and auto ML users to quickly and safely create and use business-critical data assets. Benefits go beyond democratizing data access, and even those with privileged data access are building synthetic data generators into their work flows.
