Flow assurance
The objective of this study is to field test a non-nuclear multiphase flowmeter and assess its performance under challenging operating conditions.
For more than a century, LSU has shaped petroleum engineering education, but few assets showcase its impact like the PERTT Lab. With six deep test wells and rare reservoir-depth gas-injection capabilities, the facility is helping drive breakthroughs in well control, carbon-dioxide injection, and next-generation energy technologies.
Experience in subsurface production and lift design is shaping a new generation of geothermal operations built for reliability and scalability.
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This paper is the second of a two-part series. It covers facilities problems caused by iron, injectivity problems caused by iron, and the mitigation of colloidal iron-related problems. -
The difficulty in selling a chemical to aid subsea pipeline flow has been delivering it to the wells.
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An integrated multidisciplinary work flow can improve the assessment of pipeline slugging fatigue for offshore field developments.
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Flow-assurance effects from slug-flow engineering, design, maintenance, and operations technical concerns still create and sustain challenging technical issues requiring safe, economical solutions for both onshore unconventional and offshore conventional production facilities.
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This paper describes a novel control scheme developed and tested on simulation for both hydrodynamic slugging and severe riser-induced slugging for a new facility in Angola.
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In the authors’ study, a machine-learning predictive model—boosted decision tree regression—is trained, tested, and evaluated in predicting liquid holdup in multiphase flows in oil and gas wells.
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A review of the properties of iron compounds and their impact in shale produced water treatment with an emphasis on their colloidal forms. A wide range of problems is associated with these compounds in produced water including emulsion stabilization, oil-coated solids, pad formation in separators, pipeline solids, and plugging of water disposal formations.
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The downtime of manufacturing machinery, engines, or industrial equipment can cause an immediate loss of revenue. Reliable prediction of such failures using multivariate sensor data can prevent or minimize the downtime. With the availability of real-time sensor data, machine-learning and deep-learning algorithms can learn the normal behavior of the sensor systems, dis…
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The authors present a monoethylene-glycol-sensing system and validate it in a specially constructed flow loop.
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This paper reviews innovations and technologies used to make the Atlanta field in the Santos Basin a successful case of heavy-oil production in ultradeep water.
