Data & Analytics
The DOE-backed EGS-Twin project aims to simulate geothermal production systems, helping operators better predict performance and maximize output.
This case study presents the first field deployment of acoustic fracturing analysis to evaluate perforation efficiency and implement real-time interventions during pressure pumping.
As managed pressure drilling gains traction, its principles are influencing a wider range of well-construction activities.
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This paper explores how artificial intelligence (AI), cognitive models, and integrated digital tools can transform readiness from periodic drills into a continuous, measurable capability. -
This paper presents a competency-centered, data-driven approach implemented to strengthen control-room emergency-response capability through a cloud-hosted, scenario-based virtual plant simulator.
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This paper presents an autonomous, data-driven solution designed specifically for intermittent well optimization.
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This paper describes an emergency-response system deployed on artificial islands that manages complex challenges, enhances safety protocols, and improves operational efficiency in high-risk offshore environments.
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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.
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The AI revolution isn't just digital. This article examines how geology underpins the convergence of AI, energy, carbon management, and the infrastructure powering frontier LLMs.
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SponsoredEffective data analysis depends on seeing connections that matter. Explore how Spotfire enables a more intuitive approach to understanding petroleum data.
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Schneider Electric says the deal advances its vision of creating intelligent industrial ecosystems that connect physical assets with digital insights across the asset life cycle.
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With the latest addition, the Italian major’s computational capacity passes the exaflop threshold, making the firm the world’s leading company by computing power in the new TOP500 global ranking.
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This work describes a study in which distributed data parallel training, paired with a node-local caching pipeline, enabled efficient multigraphics-processing-unit scaling for a CO₂-storage graph-neural-network surrogate while maintaining generalization.
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