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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This paper introduces a system that leverages sophisticated algorithms and user-friendly interfaces to tackle the challenge of developing complex, compartmentalized reservoirs effectively. -
The authors of this paper apply a deep-learning model for multivariate forecasting of oil production and carbon-dioxide-sequestration efficiency across a range of water-alternating-gas scenarios using field data from six legacy carbon-dioxide enhanced-oil-recovery projects.
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Experience in subsurface production and lift design is shaping a new generation of geothermal operations built for reliability and scalability.
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Switching from continuous circulation to cyclic huff-‘n’-puff operation in enhanced geothermal systems can significantly delay thermal breakthrough, sustain higher production temperatures, and improve long-term economic performance.
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The two companies say they plan to work together to use agentic AI to increase the capabilities of technical experts.
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This article is the first in a Q&A series from the SPE Methane Emissions Management Technical Section (MEMTS) on methane intelligence and how oil and gas teams translate emissions data into credible decisions and measurable reductions.
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This paper presents a robot integrated with a microcontroller that provides multiple functions to help with data logging, analysis, and reporting to identify hazards and improve safety protocols.
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Aurora Innovation and Detmar Logistics have inked a deal for 30 autonomous trucks that will begin hauling sand in the region next year.
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Sustainability in reservoir management emerges not from standalone initiatives but from integrated, data-driven workflows, where shared models, closed-loop processes, and AI-enabled insights reduce fragmentation and make sustainable performance a natural outcome.
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