gas lift
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This paper presents a case study highlighting the demonstration, refinement, and implementation of a machine-learning algorithm to optimize multiple electrical-submersible-pump wells in the Permian Basin. -
This paper presents a closed-loop iterative well-by-well gas lift optimization workflow deployed to more than 1,300 operator wells in the Permian Basin.
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This paper explores the use of machine learning in predicting pump statuses, offering probabilistic assessments for each dynacard, automating real-time analysis, and facilitating early detection of pump damage.
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ExxonMobil developed an automated system to identify nonproductive and underperforming Permian Basin wells and prioritize high-volume wells to return to production.
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This work presents the results of several failure analyses of gas lift valves retrieved from subsea wells that were unable to prevent backflow from tubing to annulus
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This paper describes laboratory tests simulating varying sour-well and extended galvanic corrosion conditions to determine the adequacy of selected armor metallurgies in downhole corrosive environments.
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This paper explores the development of fiber-reinforced thermoplastic sucker rods as a promising alternative for overcoming the limitations of steel sucker rods and thermoset fiberglass sucker rods.
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New and evolving artificial lift technology is helping operators improve production rates.
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Machine learning is refining gas lift production optimization with scalable automated workflow.
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This paper discusses a new type of mechanical gas separator for electrical submersible pump systems that increases operating flow range and separation efficiency while decreasing erosion problems and improving reliability.
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