AI/machine learning
After years of market shocks, technological breakthroughs, and rising uncertainty, ATCE 2026 will provide new insights on how industry leaders and technical experts are preparing for the next era of the upstream business.
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.
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This paper presents the application of a new automatic geosteering method that combines probabilistic interpretation with artificial intelligence for look-ahead decision-making, representing an innovative advancement in automated geosteering frameworks. -
Experts speaking at CERAWeek 2025 lauded industry's shift from focusing on the energy transition to prioritizing oil production.
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Data quality and mission clarity matter more than ever, according to experts speaking at this year’s International Petroleum Technology Conference in Kuala Lumpur.
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The massive system brings advanced capabilities for simulation, AI, and data analysis to drive breakthroughs in cancer research, materials discovery, energy technologies, and many other fields.
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The new burner, created with the help of machine learning and additive manufacturing, promises high methane destruction efficiency and combustion stability even in windy conditions.
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Transitioning to a low-carbon economy demands large-scale CO2, natural gas, and hydrogen storage. In this context, the application of AI/ML technology to uncover geochemical, microbial, geomechanical, and hydraulic mechanisms related to storage and solve complicated history-matching and optimization problems, thereby enhancing storage efficiency, has been prominently …
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The authors propose a hybrid virtual flow and pressure metering algorithm that merges physics-based and machine-learning models for enhanced data collection.
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The service giant shares new details about its automated fracturing spreads that slash human operator workload by 88%.
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The trial phase of the agentic program used AI agents and combined large-language-model technology with data collected from more than 15% of ADNOC’s onshore and offshore wells.
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SLB said it plans to integrate INT’s technology into its digital data and artificial intelligence platforms.
