Data & Analytics
The US supermajor will use Permian Basin natural gas to support the hyperscaler’s AI business.
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.
This article from the SPE Robotics and Autonomous Systems Technical Section (RASTS) explores the insights shared at the recent Offshore Technology Conference (OTC) in Houston about autonomous systems and their role in the industry's future.
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Two examples from ONGC show how supervised AI-driven automation scaled well modeling across hundreds of offshore wells, saving more than 1,000 engineering hours. -
Examples demonstrate how an Integrated Operations Center as a Service (IOCaaS) model, powered by artificial intelligence, reduced costs by 5% and increased production by 6% in Canada.
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The authors propose a deep-learning-based approach enabling near-real-time CO2-plume visualization and rapid data assimilation incorporating multiple geological realizations for predicting future CO2 plume evolution and area-of-review determination.
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In this study, the authors propose the use of a deep-learning reduced-order surrogate model that can lower computational costs significantly while still maintaining high accuracy for data assimilation or history-matching problems.
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The newest recipient of the title SPE Legend of Hydraulic Fracturing talks about his career, the evolution of fracture stimulation, the development of increasingly useful simulators, and the future of the oil and gas industry. The honor was given at the 2026 SPE Hydraulic Fracturing Technology Conference and Exhibition.
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SLB's and Baker Hughes' partnerships with NVIDIA and Google Cloud, respectively, will develop advanced AI-enabled power optimization and sustainability solutions for the global data center sector.
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ExxonMobil's Jason Gahr uses the five stages of grief to explain how the upstream industry should respond to the rise of AI.
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This paper introduces an agentic artificial-intelligence framework designed for offshore production surveillance and intervention.
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The objective of this study is to field test a non-nuclear multiphase flowmeter and assess its performance under challenging operating conditions.
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Reaching further than dashboards and data lakes, the agentic oil field envisions artificial intelligence systems that reason, act, and optimize.
