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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To analyze the status of digital transformation strategies and the pace of implementation in the Middle East, an SPE Applied Technology Workshop brought together operating and service companies and consulting firms for a discussion.
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This paper highlights the results of a test campaign for a tool designed to predict the short-term trends of energy-efficiency indices and optimal management of a production plant.
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The author argues that the advent of cloud technology should not be regarded as a further challenge to security but an opportunity to revitalize and improve a company’s defenses dramatically.
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The value of hidden-danger data stored in text can be revealed through an approach that can help sort and interpret information in an ordered way not used previously in safety management.
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Concern has been growing in the oil and gas industry about the high frequency of mooring line failures. While physical tension sensors can be difficult and costly to maintain, machine learning has shown to be a more-accurate and less-costly method for structural integrity assessment.
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Digital is replacing manual at Sanchez Oil & Gas. Since its implementation in 2017, the company’s Production Maintenance Tracker application has been transforming its operations management by bringing together all the assets, departments, and routes into one hub.
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Photogrammetry—stitching together images to create photorealistic 3D models—can be part of a larger industrial digitalization strategy that aims to liberate data from its silos, connect it to other relevant information, and make it available to the workers who need it.
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The era of Big Data is coming to an end as the focus shifts from how we collect data to processing that data in real-time. Big Data is now a business asset supporting the next eras of multicloud support, machine learning, and real-time analytics.
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Shell is continuing its exploration of blockchain with yet another investment in the technology, this time investing in LO3, a startup using a modified version of the Ethereum blockchain to make it easier for individuals to buy and sell locally produced energy.
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Digital transformation: It’s a phrase that seems to be on the lips of everyone in the oil and gas industry, and that was certainly true at the inaugural Energy in Data conference held in Austin. The conference, however, showed that the transformation is more than on its way. It’s here.