AI/machine learning
Case studies from Devon Energy, ConocoPhillips, and others show how clever engineering and technology are being used to improve recovery and asset value.
Novel lift systems, AI-driven automation, and real-time engineering models are helping operators extract more value from mature wells.
This case study from Tomax outlines the use of artificial intelligence to analyze high-fidelity data of the full drilling process.
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This paper describes a deep-learning image-processing model that uses videos captured by a specialized optical gas-imaging camera to detect natural gas leaks. -
In this study, a deep-neural-network-based workflow with enhanced efficiency and scalability is developed for solving complex history-matching problems.
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Whether it’s reviving inactive gas-condensate wells or identifying overlooked reserves in brownfields, operators are making the most of older wells and fields.
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The company said that adding Altair technology to its Xcelerator open digital business platform will create the world’s most complete AI-powered portfolio of industrial software.
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This paper introduces a novel optimization framework to address CO2 injection strategies under geomechanical risks using a Fourier neural operator-based deep-learning model.
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The energy-focused LLM project by Aramco Americas, SPE, and i2k Connect has entered the testing phase and is on track for licensing to operators later this year.
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The agreement aims to bring the efforts of both companies together to advance digital-enabled carbon-free floating power generation.
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A roundtable discussion during CERAWeek pointed to the necessity of a mindset shift for the oil and gas industry to tap into AI’s true potential.
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This paper presents the application of a new automatic geosteering method that combines probabilistic interpretation with artificial intelligence for look-ahead decision-making, representing an innovative advancement in automated geosteering frameworks.
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Experts speaking at CERAWeek 2025 lauded industry's shift from focusing on the energy transition to prioritizing oil production.
