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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Aberdeen Renewable Energy Group and the European Space Agency have signed a memorandum of intent to analyze, develop, and implement space-enabled technology and services to support the renewable energy sector. -
With such uses as tracking the source of renewable energy and changing the relationship between how energy is produced and consumed, blockchain has the potential to transform the way companies collaborate and interact to accelerate the development of low-carbon energy.
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How can the famous Casino-inspired trick for data science, statistics, and all of science be done in Python?
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Over the years, I’ve noticed interesting cultural differences between industrial sectors in their approach to dealing with staff software training. Here, I’ll try to synthesize them into a major insight and expound on the implications.
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The complete paper uses 3,782 unconventional horizontal wells to analyze the effect of proppant volume and the length of the perforated lateral on short- and long-term well productivity across the Permian Basin.
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In the spectrum of artificial intelligence (AI) technologies, those adopted to date in the oil and gas industry are task-focused, narrow applications. Taking AI to the next level cannot be done by Silicon Valley alone.
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In the complete paper, the authors generate a model by using an artificial-neural-network (ANN) technique to predict both capillary pressure and relative permeability from resistivity.
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Eni and IBM developed a cognitive engine exploiting a deep-learning approach to scan documents, searching for basin geology concepts and extracting information about petroleum system elements.
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COVID-19 has significantly accelerated the adoption of digital technologies across all industries, and the oil and gas industry has been no exception. As such, interest in digital data acquisition, which is the backbone of all digital transformation work flows, also has increased significantly.
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Industrial robots are becoming an increasingly popular choice in a variety of industries for different applications. Going by responses to a McKinsey and Company survey, up to 88% of businesses worldwide intend to adopt robotic automation into their infrastructure.
