AI/machine learning
This research focuses on combining physics-based expert rules with machine learning to improve the detection of failure-related events in electrical submersible pumps.
A combination of physics principles and machine-learning techniques is used in this work to develop a virtual flowmeter for oil-production optimization in electrical-submersible-pump-lifted oil wells, resulting in reliable generalization.
After years of market shocks, technological breakthroughs, and rising uncertainty, ATCE 2026 will provide new insights on how industry leaders and technical experts are preparing for the next era of the upstream business.
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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. -
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.
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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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Analysis by the energy research firm sees the value of artificial intelligence growing for exploration and production companies, but the company said increased investment will be necessary.
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Chevron and Halliburton describe how they built and deployed the fully autonomous closed-loop fracturing system that enables subsurface-driven optimization.
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Aramco says it has saved $770 million over the past 3 years from the $70 million it has invested over the same period in corrosion management technologies.
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The deal adds physics-based reservoir modeling and real-time decision workflows to SLB’s digital portfolio.
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Working with Dell Technologies and NVIDIA, the French supermajor is targeting improved seismic processing and artificial intelligence applications.
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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.
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AI‑driven data center growth is straining US power grids and accelerating interest in enhanced geothermal systems as a scalable, low‑carbon solution.
