AI/machine learning
Known as Arena, the collaboration aims to improve decision-making across increasingly complex reservoirs and growing volumes of subsurface data.
Robotic and autonomous systems are transforming energy operations, but their full value emerges only when paired with data science, engineering analytics, and AI/ML to turn data into decisions. The transition of the SPE Robotic & Autonomous Systems Technical Section into the SPE Data Science & Engineering Analytics Technical Section helps bridge this critical technolo…
A credible custody-transfer record depends on far more than the accuracy of a single meter. It is the product of an integrated measurement chain. While meter performance supports measurement-system integrity, commercial confidence also depends on traceability, governance, and authorization.
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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. -
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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The full potential of data can only be realized when it is viewed not in isolation but as part of the dynamic triad of hydrocarbons, the data, and the people who interpret it and act on it.
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Over decades of exploration and production, the oil and gas sector has accumulated vast amounts of legacy data in various formats. Artificial intelligence and machine learning present an opportunity to transform how this unstructured data is processed and used, enabling significant improvements in operational efficiency and decision-making.
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SLB will use artificial intelligence-based software to help ensure the delivery of 18 ultradeepwater wells.
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This paper describes a deep-learning image-processing model that uses videos captured by a specialized optical gas-imaging camera to detect natural gas leaks.
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In this study, a deep-neural-network-based workflow with enhanced efficiency and scalability is developed for solving complex history-matching problems.
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Whether it’s reviving inactive gas-condensate wells or identifying overlooked reserves in brownfields, operators are making the most of older wells and fields.
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The company said that adding Altair technology to its Xcelerator open digital business platform will create the world’s most complete AI-powered portfolio of industrial software.
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This paper introduces a novel optimization framework to address CO2 injection strategies under geomechanical risks using a Fourier neural operator-based deep-learning model.
