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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A recent cyberattack on a data processing system used by many US pipelines could be a prelude to more severe disruptions, cybersecurity experts said.
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Advanced AUVs with early-stage technologies for live streaming, ultrasonic testing, and 3D laser scanning are set to enter inspection trials on North Sea facilities. The aim is to reduce facilities inspection costs by 50%. -
Oil companies fell behind in hardening their computer control systems against cyberattacks after the collapse of crude prices more than 3 years ago, according to cybersecurity experts.
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The world is digitalizing all around us. Within the energy sector, the lower-price environment since 2014 has increased the pace of change and the scope of digital integration. But, are you bringing your people strategy along?
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At least four US pipeline companies have seen their electronic systems for communicating with customers shut down over the last few days, with three confirming it resulted from a cyberattack.
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An 18-month project will develop and trial a mobile robot for autonomous operational inspection of Total facilities.
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A cyberattack on a third-party provider of an electronic data interchange platform temporarily interrupted Energy Transfer Partners’ ability to transfer files with its customers.
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The goal of cognitive computing is not to eliminate humans but allow highly skilled professionals to spend time doing what’s most valuable for the company.
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In the complete paper, the authors propose a novel method to rapidly update the prediction S-curves given early production data without performing additional simulations or model updates after the data come in.
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The aim of this work is to present the effectiveness of a fully integrated approach for ensemble-based history matching on a complex real-field application.
