Data & Analytics
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.
Novel lift systems, AI-driven automation, and real-time engineering models are helping operators extract more value from mature wells.
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In this work, a methodology to detect interference from long-term pressure and flow-rate data is developed using multiresolution analysis in combination with machine-learning algorithms. -
SponsoredImprove decision making and reduce the uncertainty of CCS projects with accurate, detailed subsurface insights that help you estimate storage capacity, run play chance mapping, improve your injection strategy, and simulate carbon plumes over time.
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The web-based tool may be applied throughout an energy project's life cycle.
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Ultimately, the company formerly known as Facebook wants the AI Research SuperCluster system to help it develop artificial intelligence to power the metaverse.
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A two-armed autonomous underwater vehicle has been launched for complex inspection and maintenance tasks, embedded in a powerful IT infrastructure that enables both intuitive control and monitoring of the system and effective information flow with the plant operator.
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Applications include identifying new green catalysts to enable the conversion of waste products to useful matter, green hydrogen generation, CO2 utilization, and the development of fuel cells. Novel catalysts also could be used to replace expensive and rare materials such as iridium, the metal used to generate green hydrogen and CO2 reduction products.
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Are your skilled innovators not performing as quickly as you thought they would? I think I know why.
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This selection of papers will familiarize facilities engineers with a variety of topics so they are more prepared for what 2022 may bring.
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The authors present a review of the capabilities of fog computing and its potential in the petroleum industry.
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The machine-learning techniques applied aim to deliver a prediction model based on both simulation and real-time field data. The model tracks and monitors system key performance indicators.
