AI/machine learning
Case studies from Devon Energy, ConocoPhillips, and others show how clever engineering and technology are being used to improve recovery and asset value.
Novel lift systems, AI-driven automation, and real-time engineering models are helping operators extract more value from mature wells.
This case study from Tomax outlines the use of artificial intelligence to analyze high-fidelity data of the full drilling process.
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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. -
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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The service giant shares new details about its automated fracturing spreads that slash human operator workload by 88%.
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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 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.
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Chevron’s announcement comes on the heels of ExxonMobil’s announcement in December of a similar project to deliver natural gas-fueled electricity to US data centers.
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The authors make the case that data science captures value in well construction when data-analysis methods, such as machine learning, are underpinned by first principles derived from physics and engineering and supported by deep domain expertise.
