AI/machine learning
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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The massive system brings advanced capabilities for simulation, AI, and data analysis to drive breakthroughs in cancer research, materials discovery, energy technologies, and many other fields. -
The new burner, created with the help of machine learning and additive manufacturing, promises high methane destruction efficiency and combustion stability even in windy conditions.
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Transitioning to a low-carbon economy demands large-scale CO2, natural gas, and hydrogen storage. In this context, the application of AI/ML technology to uncover geochemical, microbial, geomechanical, and hydraulic mechanisms related to storage and solve complicated history-matching and optimization problems, thereby enhancing storage efficiency, has been prominently …
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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.
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The service giant shares new details about its automated fracturing spreads that slash human operator workload by 88%.
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The trial phase of the agentic program used AI agents and combined large-language-model technology with data collected from more than 15% of ADNOC’s onshore and offshore wells.
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SLB said it plans to integrate INT’s technology into its digital data and artificial intelligence platforms.
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Chevron’s announcement comes on the heels of ExxonMobil’s announcement in December of a similar project to deliver natural gas-fueled electricity to US data centers.
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From optimizing drilling performance to enhancing worker safety, computer vision can change how the industry works.
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The authors make the case that data science captures value in well construction when data-analysis methods, such as machine learning, are underpinned by first principles derived from physics and engineering and supported by deep domain expertise.
