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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With so many buzzwords surrounding artificial intelligence and machine learning, understanding which can bring business value and which are best left in the laboratory to mature is difficult. -
Despite having some of industry’s most hazardous working environments, a sector that pioneered the adoption of digital technology has been slow to exploit artificial intelligence and machine learning in the area of health and safety.
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This paper details how artificial intelligence was used to capture analog field-gauge data with a dramatic reduction of cost and an increase in reliability.
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Major differences exist between engineering- and nonengineering-related problems. This fact results in major differences between engineering and nonengineering applications of artificial intelligence and machine learning.
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Joelle Pineau, a machine-learning scientist at McGill University, is leading an effort to encourage artificial-intelligence researchers to open up their code.
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This paper investigates the most important independent variables, including petrophysics and completion parameters, to estimate ultimate recovery with a machine-learning algorithm. A novel machine-learning model based on random forest regression is introduced to predict estimated ultimate recovery.
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What is explainability in artificial intelligence, and how can we leverage different techniques to open the black box of AI and peek inside? This practical guide offers a review and critique of the various techniques of interpretability.
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Leaders in the AI community came together to release the 2019 AI Index report, an annual attempt to examine the biggest trends shaping the AI industry, breakthrough research, and AI’s impact to society.
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The media is often tempted to report each tiny new advance in a field, be it artificial intelligence or nanotechnology, as a great triumph that will soon fundamentally alter our world. Occasionally, of course, new discoveries are underreported.
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Using deep-learning and computer-vision techniques, the software recognizes all instances of specific instruments, valves, lines, and other features in a P&I diagram in seconds.
