AI/machine learning
The authors write that deployment of artificial-intelligence-based high-gas/oil ratio well-control technology enabled stabilization of well performance and maintenance of optimal production conditions.
This paper presents the first global application of autonomous drilling in deepwater and the journey to reach optimal drilling parameters, integrating proprietary tools from the project’s business partners.
EQT is benchmarking its way to basin-leading productivity and relying on partnerships and new technology to turn KPIs into operational reality.
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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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Secondary and tertiary efforts are critical for sustaining the productive lives of unconventional plays.
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Foundation models are rapidly emerging as a transformative force across industries. While their effect on natural language processing and computer vision is well-documented, their potential in specialized engineering domains, particularly within the critical oil, gas, and broader energy sectors, is vast and increasingly recognized. This article explores how these powe…
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Buoy-based camera footage, analyzed by artificial intelligence, can help reduce the risk of birds colliding with offshore wind farm turbines.
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Best practices are not static; they evolve alongside advancements that redefine what is achievable.
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New strides in computer vision, well controls indicators, and BOP alignment were showcased at the recent Offshore Technology Conference.
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Gautam Swami, manager of corporate R&D at NOV and SPE member, shares his experiences in building a career in oil and gas R&D, discusses how innovation is shaping the industry, and offers guidance to young professionals.
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Aramco’s latest MOUs focus on driving innovation and growth across oil, gas, and downstream sectors.
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This article presents a comparative study evaluating four machine-learning approaches, including three deep-learning methods, for forecasting gas and condensate production over a 5-year horizon.