Data & Analytics
Working with Dell Technologies and NVIDIA, the French supermajor is targeting improved seismic processing and artificial intelligence applications.
A discussion at the inaugural executive breakfast convened by the SPE Data Science and Engineering Analytics Technical Section, held alongside CERAWeek by S&P Global and powered by Black & Veatch, tackled the challenge of value creation from artificial intelligence in the energy industry.
AI‑driven data center growth is straining US power grids and accelerating interest in enhanced geothermal systems as a scalable, low‑carbon solution.
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Technology and partnerships play a pivotal role in how the oil industry finds and produces energy from frontier regions and brownfields, both now and in the future. -
Data quality and mission clarity matter more than ever, according to experts speaking at this year’s International Petroleum Technology Conference in Kuala Lumpur.
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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.
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B3 Insight and Nanometrics plan to integrate data from seismic monitoring with a water and subsurface data analytics platform.
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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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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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In the Marcellus, Repsol is slicing and dicing legacy data to evolve its completions strategy, while in the Permian, ExxonMobil is mastering the 4-mile lateral drillout using lessons learned.
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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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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.
