Data & Analytics
This research focuses on combining physics-based expert rules with machine learning to improve the detection of failure-related events in electrical submersible pumps.
A combination of physics principles and machine-learning techniques is used in this work to develop a virtual flowmeter for oil-production optimization in electrical-submersible-pump-lifted oil wells, resulting in reliable generalization.
This paper presents the deployment of an artificial intelligence-enabled autonomous gas lift optimization system, integrating real-time centralized advanced process control with cloud-based analytics to enhance artificial gas lift performance in producer wells.
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Organic data governance emphasizes flexibility, stakeholder engagement, and a culture that values data integrity.
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SLB will use artificial intelligence-based software to help ensure the delivery of 18 ultradeepwater wells.
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A robotic arm, camera system, and virtual reality helped EniProgetti and University of Naples researchers overcome the major challenges of direct-contact nondestructive testing using a drone.
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Shell’s combination of digital worker technologies enables collaborative troubleshooting and inspections while reducing travel and boosting efficiency.
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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.
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The energy-focused LLM project by Aramco Americas, SPE, and i2k Connect has entered the testing phase and is on track for licensing to operators later this year.