AI/machine learning
This paper explores how artificial intelligence (AI), cognitive models, and integrated digital tools can transform readiness from periodic drills into a continuous, measurable capability.
This paper presents an autonomous, data-driven solution designed specifically for intermittent well optimization.
From AI-enabled walking rigs to subsea drones and autonomous inspection robots, robotics is rapidly moving from pilot projects to field deployment. The technology promises not only greater efficiency but also a fundamental shift in how the industry approaches safety and asset management.
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Best practices are not static; they evolve alongside advancements that redefine what is achievable. -
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.
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After a successful trial phase of ENERGYai, AIQ has been tapped to roll out the technology across ADNOC’s upstream operations.
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Weatherford and AIQ say they aim to enable the energy sector to unlock efficiencies, boost productivity, and reduce operational costs by combining their strengths.
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The rapid development of oil and gas intelligent operations depends on artificial intelligence, automation, and data analytics to achieve optimal conditions in oil and gas operations.
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This article is the second in a Q&A series from the SPE Research and Development Technical Section focusing on emerging energy technologies. In this piece, Madhava Syamlal, CEO and founder of QubitSolve, discusses the present and future of quantum computing.
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This paper presents an immersive platform that enables multidisciplinary teams and management to make decisions, connecting professionals to demonstrate and share findings in a way that capitalizes on artificial intelligence and cognitive capabilities.
