DSDE: In Practice
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The complete paper demonstrates the benefits of honoring data measurements from a multitude of potential sources to help engineers do a better job of including more diagnostics into routine operations to provide additional insight and result in improved models and completion designs.
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An AI-based application enabled operators to preempt ESP failures while optimizing production.
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Time-stamped data anomalies can lead to more-accurate identification and faster diagnosis.
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The complete paper presents a discussion of the use of intelligent well completion in Santos Basin Presalt Cluster wells.
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This paper presents a fatigue-prediction methodology designed to extend the life of unbonded flexible risers and improve the accuracy of floating production, storage, and offloading vessel response analysis.
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A real-time deep-learning model is proposed to classify the volume of cuttings from a shale shaker on an offshore drilling rig by analyzing the real-time monitoring video stream.
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AltaML has announced a partnership with engineering and design firm Kleinfelder in which the two companies will pair 3D reality scans of facilities with artificial intelligence to look for potential problems and risks.
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Researchers with the National Center for Airborne Laser Mapping at the University of Houston are creating a set of algorithms that would allow users to more-precisely align data sets collected at different times and reliably estimate changes between images captured at different times.
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An estimate says data centers, including edge sites, will soon use four times the energy all data centers used in 2018. Can it be true?
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In this paper, the authors introduce a new technology installed permanently on the well completion and addressed to real-time reservoir fluid mapping through time-lapse electromagnetic tomography during production or injection.
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