Data & Analytics
This paper presents a smart safety monitoring system to prevent accidents in environments with moving machinery at use on various global rigs.
The Energy and AI Observatory aims to use up-to-date information on energy demand from data centers to determine how artificial intelligence is optimizing the energy sector.
The company is making available its data on ocean and weather conditions in an effort to boost transparency and innovation.
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Schlumberger announced that ConocoPhillips will use its DELFI platform to move its data to the cloud. -
A recent survey sponsored by ABS Group revealed that 45% of participants estimate the threats to their control systems are high and another 15% said they were severe or critical.
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The authors write that the application of electrical parameters to diagnose working conditions and meter production of pumping wells is the key to the low-cost Internet-of-Things construction.
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This paper describes a novel machine-learning approach for processing distributed fiber-optic sensing data that enables dynamic flow-profile monitoring using a fiber-optic electric-line cable deployed in a gas condensate well.
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The authors provide a comparison of wireless telemetry methods and discuss potential improvements to existing systems.
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The paper describes a project automating the progressing-cavity-pump well-modeling process wherein models are built and sustained automatically in a well-management system for all active PCP wells.
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Rodolfo Camacho-Velázquez identifies areas of opportunity for future reservoir engineers related to the technical challenges of increased production and recovery of complex conventional and unconventional reservoirs, the application of Fourth Industrial Revolution technologies in reservoir subdisciplines, and the energy transition.
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Microsoft's Azure and Research teams are working together on the Singularity artificial-intelligence infrastructure service.
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The initiative is designed to support national data repositories, regulators, and national oil companies looking for ways to leverage, maintain, and improve their data.
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Dozens of startups continue to get tens of millions in venture funding to make chips for AI in mobile and other embedded computing uses. The race shows no sign of slowing down.
