Data & Analytics
This research focuses on combining physics-based expert rules with machine learning to improve the detection of failure-related events in electrical submersible pumps.
A combination of physics principles and machine-learning techniques is used in this work to develop a virtual flowmeter for oil-production optimization in electrical-submersible-pump-lifted oil wells, resulting in reliable generalization.
This paper presents the deployment of an artificial intelligence-enabled autonomous gas lift optimization system, integrating real-time centralized advanced process control with cloud-based analytics to enhance artificial gas lift performance in producer wells.
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The company is making available its data on ocean and weather conditions in an effort to boost transparency and innovation. -
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.
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This article is the third in a Q&A series from the SPE Research and Development Technical Section focusing on emerging energy technologies. In this piece, Zikri Bayraktar, a senior machine learning engineer with SLB’s Software Technology and Innovation Center, discusses the expanding use of artificial intelligence in the upstream sector.
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This article presents a results-driven case study from an ongoing collaboration between a midstream oil and gas company and Neuralix Inc.
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As carbon capture scales up worldwide, the real challenge lies deep underground—where smart reservoir management determines whether CO₂ stays put for good.
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The SPE Reservoir Technical Discipline and Advisory Committee invite their Reservoir members worldwide to participate in a new survey aimed at assessing the current state of reservoir engineering across industry and academia. Deadline is 21 July 2025.
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The agreement focuses on improving operational efficiency and consistency through advanced digital tools and real-time data integration.
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TotalEnergies and the French company Mistral AI are joining forces to extend the use of AI in improving TotalEnergies’ performance, especially in low-carbon energies. The partners plan to set up a joint innovation lab focused on artificial intelligence.
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Operators that demand control of their future position in global energy production are forging ahead into new territory by digitally transforming their operations at a time that still feels relatively comfortable. They’ve recognized that, while traditional approaches served the industry well for many decades, the chance to reimagine how they do things is not something…
