AI/machine learning
The emerging vision is an industry where engineers focus on judgment, risk assessments, and accountability.
This study demonstrates the transformative potential of physics-informed neural networks as a hybrid framework for multiphase flow measurement.
Case studies from Devon Energy, ConocoPhillips, and others show how clever engineering and technology are being used to improve recovery and asset value.
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This paper describes an experimentation trial deploying and operating a computer-vision system on a deepwater rig to measure drilled cuttings in real time using a remotely monitored camera system. -
Real-time wellhead monitoring aims to help Romania meet new EU methane emission regulations.
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The supermajor’s Energy Outlook 2025 suggests geopolitical fragmentation could tilt the balance of the energy trilemma toward energy security and away from sustainability.
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The companies said they plan to start deploying digital twin technologies in Oman this year.
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Oil and gas experts encourage human/AI partnerships that can “supercharge” capabilities to create competitive advantages.
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This paper presents a novel workflow with multiobjective optimization techniques to assess the integration of pressure-management methodologies for permanent geological carbon dioxide storage in saline aquifers.
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This paper reviews the motivation and development of response-based forecasting from the perspective of the authors, reviewing examples and processes that have served as validation and led to modeling refinement.
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This paper introduces a technology for offshore pipeline inspection centered on an autonomous robotic system equipped with underwater computer vision and edge-computing capabilities.
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Deploying artificial intelligence across an enterprise requires thinking beyond the pilot.
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The fifth edition of the SPE Europe Energy GeoHackathon, beginning on 1 October, focuses on how data science can advance geothermal energy and drive the energy transition.
