AI/machine learning
The DOE-backed EGS-Twin project aims to simulate geothermal production systems, helping operators better predict performance and maximize output.
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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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.
