Data & Analytics
After years of market shocks, technological breakthroughs, and rising uncertainty, ATCE 2026 will provide new insights on how industry leaders and technical experts are preparing for the next era of the upstream business.
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.
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During transfer learning, the knowledge gained and rapid progress made from a source task is used to improve the learning and development to a new target task. -
Software company FutureOn and consulting firm Wood are working together on an enhanced digital service for asset operators.
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The authors present an artificial-intelligence and machine-learning technology to obtain a high-level, comprehensive view of all equipment in a facility to detect and map corrosion.
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It appears to be possible to sense how fractures change during production using ultrasensitive fiber-optic strain measurements.
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This paper provides an alternative solution to identifying, classifying, and vertically distributing fractures and a lateral distribution method for reservoir modeling.
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The paper demonstrates the ability of deep-learning generative models to enable new shale-characterization methods.
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This paper describes a method to determine rig state from camera footage using machine-learning-based vision-analytics approaches.
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This third installment of the Digital Data Acquisition Technology Focus will focus on computer vision for improved data acquisition. Computer vision is defined as a field of study that seeks to develop techniques to help computers “see” and understand the content of digital images such as photographs and videos.
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SponsoredEach well drilled, stimulated, and completed represents a significant investment in time, resources, and expenses. From artificial lift system design to maintenance scheduling, maximize your investment by ensuring optimal flow and production throughout the life cycle.
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Integrating physics and machine learning combines the best of the two worlds, resulting in higher accuracy, better scalability, and cost efficiency.
