Data & Analytics
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.
This case study describes how edge computing and industrial internet of things platforms were deployed to automate and optimize production operations across four distinct basins.
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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Traditionally, the drilling industry has relied on high-fidelity thermal simulators to predict downhole temperature for different operational scenarios. Though accurate, these models are too slow for real-time applications. To overcome this limitation, a deep-learning solution is proposed that enables fast, accurate prediction of downhole temperatures under a wide ran… -
This article explores how the pursuit of a "perfect" reservoir model may be hindering progress in an industry increasingly shaped by data, uncertainty, and AI.
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Almost all rigs, platforms, and vessels have some form of cellular mobile services, fiber, or even microwave transmission. Nevertheless, all these vessels and assets are equipped with satellite connectivity capabilities.
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The company, as part of joint industry projects, has released an updated version of its computational fluid dynamics software that it says will aid in developing technology for the energy transition.
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The companies are joining forces to work on large-scale industrial data collection across TotalEnergies’ operational sites, aiming to use continuous, real-time data collection to optimize performance.
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This paper presents a smart safety monitoring system to prevent accidents in environments with moving machinery at use on various global rigs.
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The Energy and AI Observatory aims to use up-to-date information on energy demand from data centers to determine how artificial intelligence is optimizing the energy sector.
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The company is making available its data on ocean and weather conditions in an effort to boost transparency and innovation.
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The nonprofit said the satellite likely is unrecoverable but that it will continue to analyze the data it had collected.
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This research developed a clear framework for assessing and selecting fit-for-purpose software. The study focuses on the role of a data-driven approach in the decision process, with application to operational software systems in the oil and gas industry.
