AI/machine learning
The deals, with a potential value exceeding $3.7 billion, are aimed at strengthening Saudi Aramco’s supply chains and expanding its use of industrial artificial intelligence.
This work applies fuzzy logic, a well-established artificial-intelligence technique, to quantitatively assess connectivity between injectors and producers in a giant presalt field in the Santos Basin of Brazil.
The DOE-backed EGS-Twin project aims to simulate geothermal production systems, helping operators better predict performance and maximize output.
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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. -
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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In the past year, publications on CO2, natural gas, and hydrogen storage have increasingly focused on the design, evaluation, and optimization of storage plans. These efforts encompass a broad spectrum of challenges and innovations, including the expansion of storage reservoirs from depleted gas fields and saline aquifers to stratified carbonate formations and heavy-o…
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Reaching further than dashboards and data lakes, the agentic oil field envisions artificial intelligence systems that reason, act, and optimize.
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Major increases in hydrocarbon production require both incremental and revolutionary technologies, industry leaders said during the SPE Hydraulic Fracturing Technology Conference.
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This paper presents an automated workflow deployed for scheduling and validating steady-state production-well tests across more than 2,300 wells in the Permian Basin.
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This paper presents a multifaceted approach leveraging precise rig control, physics models, and machine-learning techniques to deliver consistently high performance in a scalable manner for sliding.
