Digital Oil Field
Reaching further than dashboards and data lakes, the agentic oil field envisions artificial intelligence systems that reason, act, and optimize.
This paper presents a robust workflow to identify optimization opportunities in gas lift wells through real-time data analysis and a surveillance-by-exception methodology.
This paper introduces an agentic artificial-intelligence framework designed for offshore production surveillance and intervention.
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Harnessing stranded data will transform operations beyond what existing, siloed software solutions delivered. There is a clear need to be more agile and embrace cloud-based solutions to realize new capabilities. -
The goal is to support the development and sharing of best-practice approaches for project delivery and asset operations using cloud services and digital workflows in engineering and operations.
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Acquiring data from an abandoned subsea well has been done before, but never quite like this.
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Wearable computers are turning heads in the oil and gas industry and appear to be on a trajectory for widespread adoption.
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A producer and a service company have collaborated to develop a downhole system to merge multilateral technology and intelligent completions to create “smart laterals.”
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What I find impressive is the number of people who were hiding in normal discipline jobs who are coming out of the closet with their Python scripts. And, it’s working. In many ways, order is coming to the mess, efficiency is coming to tiresome manual activities, and richness is coming to decisions.
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The authors present a new data-driven approach to estimate the injection rate in all noninstrumented wells in a large waterflooding operation accurately.
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In the complete paper, the authors propose a novel method to rapidly update the prediction S-curves given early production data without performing additional simulations or model updates after the data come in.
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The aim of this work is to present the effectiveness of a fully integrated approach for ensemble-based history matching on a complex real-field application.
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Since the first intelligent completion was installed 20 years ago, the systems have become increasingly complex in order to reach productivity and optimization goals, allowing real-time independent monitoring and management of each zone in the well.
