AI/machine learning
The emerging vision is an industry where engineers focus on judgment, risk assessments, and accountability.
Case studies from Devon Energy, ConocoPhillips, and others show how clever engineering and technology are being used to improve recovery and asset value.
This study demonstrates the transformative potential of physics-informed neural networks as a hybrid framework for multiphase flow measurement.
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This paper describes an auto-adaptive workflow that leverages a complex interplay between machine learning, physics of fluid flow, and a gradient-free algorithm to enhance the solution of well-placement problems. -
This paper presents a novel application of artificial intelligence in computer vision for automating blowout-preventer pressure-chart-data extraction, demonstrating significant efficiency gains and a high return on investment.
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Aurora Innovation and Detmar Logistics have inked a deal for 30 autonomous trucks that will begin hauling sand in the region next year.
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Sustainability in reservoir management emerges not from standalone initiatives but from integrated, data-driven workflows, where shared models, closed-loop processes, and AI-enabled insights reduce fragmentation and make sustainable performance a natural outcome.
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SponsoredIn oil and gas operations, every decision counts. For more than 2 decades, SiteCom has been the trusted digital backbone for well operations worldwide, driving insight, collaboration, and efficiency.
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This study presents a novel hybrid approach to enhance fraud detection in scanned financial documents.
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This paper describes a machine-learning approach to accurately flag abnormal pressure losses and identify their root causes.
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Even as industry faces policy and tariff uncertainty, companies view spending on digital transformation as a driver of efficiency.
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The Tela artificial intelligence assistant is designed to analyze data and adapt upstream workflows in real time.
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In this third work in a series, the authors conduct transfer-learning validation with a robust real-field data set for hydraulic fracturing design.
