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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ROVs dominate the world of subsea inspections, maintenance, and repair, but as operators work in a post-downturn economy, autonomous systems have become more in demand. Autonomous inspections are possible today, but how can they help with light and heavy intervention?
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Research has found that most cyberattacks against the energy and utilities industry transpire and thrive inside enterprise information-technology networks rather than critical infrastructure.
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Data-driven methods offer significant advantages in the industry, under certain conditions, over conventional methods. But reservations still exist about their use. The paper serves to bridge the gap between unclear understanding of these methods and their successful acceptance and implementation.
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The use of data-intensive decision making and smart risk-management solutions has resulted in the improvement of the ethical foundations underlying the industry. These digital tools and machine-based cognitive processes for risk-avoidance have also helped restore the public’s trust in the industry.
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Remote condition monitoring of offshore platform equipment tracks performance data, watching for deviations from baseline benchmarks. Unexpected variances can be investigated and serviced by technicians dispatched to target the root causes—an approach called condition-based maintenance.
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Digitalization in operating, maintaining, and upgrading subsea plants to reduce cost includes making information available to the control-room operator, reducing alarms, tuning the control system for optimal performance, condition monitoring, and condition-based maintenance.
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Digitalization in the oil and gas industry has been the focus of much discussion, but little has been written on the slow rate of adoption. This paper outlines some of the barriers the industry faces as it assimilates into Industry 4.0—automation and data integration in manufacturing.
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Cyberattacks are often seen as an IT issue, but the intelligence gained during the development of an effective cybersecurity protocol may serve a broader role as a business driver for energy. What should companies look for in assessing threats?
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BHGE is developing an analytics and machine-learning approach that offers descriptive and predictive insights on frac hits, with the aim of eventually offering a real-time monitoring capability to be deployed during frac jobs.
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The execution of process automation projects depends on the completion of tasks that are not necessarily related to automation, hampering project development timelines. How do automation solutions, such as digital twins, help to overcome these challenges?