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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This paper describes the development and field trials of a cloud-connected, wireless intelligent completion system that enables long-term monitoring and interval control to enhance production management by connecting the user wirelessly from the desktop to downhole inflow-control valves. -
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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Digital twins are powerful combinations of models and data that “age” throughout the lifecycle of an asset as they gather and integrate data from the field. This technology is a quantum leap from earlier efforts at modeling complex systems.
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This article outlines 10 top trending technologies for 2019, a list that covers diverse topics such as security, the Internet of things, reinforcement learning, energy sustainability, and smart cities.
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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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The international major is calling its latest multiwell project in the Permian Basin a “beacon of innovation.” The goal is to see if combining digital technologies will lower the operating costs of its shale assets.
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As companies look to reduce the time it takes to inspect a subsea pipeline, as well as the costs involved in the operation, autonomous systems have become a more desirable option. How close are they to becoming the norm?
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Innovating internal systems at Exxon inspires executives to create a forum for the oil and gas industry.
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The report focuses on the effect of data analytics on reservoir engineering applications, more specifically the ability to characterize reservoir parameters, analyze and model reservoir behavior, and forecast performance to transform the decision-making process.
