Digital Oil Field
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.
This paper presents a novel reservoir engineering/reservoir simulation approach—a data-driven interwell-connectivity model augmented as a digital twin—to predict reservoir dynamics and optimize operations in the Changqing oil field of China.
This work uses a novel pseudosteady-state-based simulation to reduce training-data-generation cost while maintaining high-performance predictions of data-driven proxy models for carbon-sequestration projects.
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Weatherford International announced a strategic agreement with Amazon Web Services (AWS) to advance the company's digital transformation and drive innovation across the energy sector.
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This paper describes the operator’s digital-twin end-to-end production system deployed for model-based surveillance and optimization.
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The authors of this paper describe a project to develop a virtual sensor to monitor the cooling effect downstream of a subsea choke to avoid hydrate plugs during cold-start operations.
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This paper presents an immersive platform that enables multidisciplinary teams and management to make decisions, connecting professionals to demonstrate and share findings in a way that capitalizes on artificial intelligence and cognitive capabilities.
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The paper showcases the digital journey of a brownfield where digital solutions are enhancing recoverable volume, production, and process efficiency while minimizing losses and maximizing the return of investment.
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The rapid development of oil and gas intelligent operations depends on artificial intelligence, automation, and data analytics to achieve optimal conditions in oil and gas operations.
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SponsoredAs operators strive to increase production under tighter budgets, traditional downhole diagnostics are falling short—too costly, complex, and time-consuming. Seismos Acoustic Friction Analysis (SAFA) offers a smarter, surface-based alternative. This white paper explores how SAFA enables real-time treatment optimization, better fracture performance, and substantial cos…
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The full potential of data can only be realized when it is viewed not in isolation but as part of the dynamic triad of hydrocarbons, the data, and the people who interpret it and act on it.
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Guest Editorial: 2025 Perspective: Digital Transformation in Oil and Gas—From Evolution to ShockwaveThe path forward is not just about automation—it is about augmentation. AI is not replacing human expertise; it is amplifying it. Those who master this balance will define the future of oil and gas in a rapidly evolving energy landscape.
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The authors propose a hybrid virtual flow and pressure metering algorithm that merges physics-based and machine-learning models for enhanced data collection.