AI/machine learning
The DOE-backed EGS-Twin project aims to simulate geothermal production systems, helping operators better predict performance and maximize output.
From AI-enabled walking rigs to subsea drones and autonomous inspection robots, robotics is rapidly moving from pilot projects to field deployment. The technology promises not only greater efficiency but also a fundamental shift in how the industry approaches safety and asset management.
This paper explores how artificial intelligence (AI), cognitive models, and integrated digital tools can transform readiness from periodic drills into a continuous, measurable capability.
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This paper outlines how one company uses digital technologies to manage HSE risks in project delivery, developing an artificial intelligence (AI) predictive model to predict HSE risks and incidents based on historical incident data. -
The RoboWell technology for well control will be available globally through Halliburton’s Landmark iEnergy hybrid cloud.
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Automated workflow unifies geological, completion, and production data to inform speedier, better investment decisions for nonoperated assets.
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Both new and old vessels are benefiting from automation processes that can improve operational efficiency, predict downtime, and debottleneck workflows using a flurry of crucial data points.
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The authors of this paper review the advantages of machine learning in complex compositional reservoir simulations to determine fluid properties such as critical temperature and saturation pressure.
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Operators tell an audience at the Unconventional Resources Technology Conference how a hybrid expandable liner system and machine-learning-based analysis improve the bottom line.
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Machine learning is refining gas lift production optimization with scalable automated workflow.
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The Permian’s produced-water challenge presents an opportunity for innovation to pave the way toward a more sustainable future for the industry.
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The chief operating officer of Chesapeake Energy tells the Unconventional Resources Technology Conference that small wins can pave the path to big achievements.
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The Norwegian major agrees to use Seeq’s software in an effort to maximize production and enhance efficiency across its assets.
