AI/machine learning
Novel lift systems, AI-driven automation, and real-time engineering models are helping operators extract more value from mature wells.
Case studies from Devon Energy, ConocoPhillips, and others show how clever engineering and technology are being used to improve recovery and asset value.
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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The authors of this paper describe a suite of technologies that enables enhanced well robustness and performance modeling and monitoring of carbon storage facilities. -
This paper presents the proof of concept of artificial-intelligence-based well-integrity monitoring for gas lift, natural flow, and water-injector wells.
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The authors of this paper present a machine-learning-based solution that predicts pertinent gas-injection studies from known fluid properties such as fluid composition and black-oil properties.
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Finding and producing crude and natural gas is far, far removed from the days of acting on a geologist’s hunch or a wildcatter’s gut feeling.
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It is imperative for energy companies to assess potential legal ramifications of integrating artificial intelligence into their operations.
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Few oil and gas companies give data science projects the better part of a decade to prove out, but that’s just what this one did.
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The company has announced that it will be expanding the use of generative AI to assist its employees.
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The oil and gas industry is embracing digital technology not just as a differentiator but as an enabler of innovation. The simple reality is that, if one doesn’t, they risk being out of the game.
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AIQ, ADNOC, and SLB announced a new software suite that integrates artificial intelligence into reservoir analysis and field development projects.
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Declining costs to launch monitoring satellites, as well as artificial intelligence, which makes parsing terabytes of emissions data feasible, have given the oil and gas industry an emerging tool for environmental stewardship.
