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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The authors develop a data-driven approach, enabled by machine learning, to find an optimal operating envelope for gas-lift wells. -
The authors describe an integrated geological-engineering data-management project covering all aspects of well-engineering work flows.
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The paper demonstrates the application of an interpretable machine-learning work flow using surface drilling data to identify fracable, brittle, and productive rock intervals along horizontal laterals in the Marcellus shale.
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SponsoredAre you ready? Data is an enterprise asset, underlying your ability to deliver on your commitments. But are you deploying it in ways that serve your strategic goals? Datagration makes the case for changing how you think about data management.
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Two Houston-based blockchain technology companies—Data Gumbo and Topl—are collaborating to help corporations report timely and accurate environmental, social, and governance (ESG) data, including performance and proof of progress on metrics, while protecting sensitive data.
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The ethics of artificial intelligence (AI) has become an important topic in the application of AI and machine learning in the past several years. This first part of a two-part series explains the evolution and importance of the ethics of AI. The second part will present its relevance and use in engineering applications.
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Using electricity to run oilfield operations is supposed to make everything better, but just getting the power needed is a challenge.
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The collaboration will combine Lytt’s fiber-optic data analytics and cloud-based software with Baker Hughes’ completions and well intervention hardware.
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The downtime of manufacturing machinery, engines, or industrial equipment can cause an immediate loss of revenue. Reliable prediction of such failures using multivariate sensor data can prevent or minimize the downtime. With the availability of real-time sensor data, machine-learning and deep-learning algorithms can learn the normal behavior of the sensor systems, dis…
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Hiber, an industrial Internet-of-Things startup, announced that it has signed an agreement with Shell to provide well-integrity monitoring solutions globally.
