Data & Analytics
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.
This paper presents the deployment of an artificial intelligence-enabled autonomous gas lift optimization system, integrating real-time centralized advanced process control with cloud-based analytics to enhance artificial gas lift performance in producer wells.
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This paper demonstrates how the integration of multiphysics downhole imaging with machine-learning techniques provides a significant advance in perforation-erosion analysis. -
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 presents a robust workflow to identify optimization opportunities in gas lift wells through real-time data analysis and a surveillance-by-exception methodology.
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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.
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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…
