Flow assurance
This paper describes the successful deployment of flexible coiled tubing technology in an oil-producing well of the offshore Frade field in Brazil’s Campos Basin.
This case study from Italian technology developer Sentris highlights the effectiveness of using sensors during pigging operations to optimize cleaning efficiency.
The objective of this study is to field test a non-nuclear multiphase flowmeter and assess its performance under challenging operating conditions.
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Aramco investigates expanding the use of lasers in the upstream sector of the oil field. -
This case study demonstrates an estimated cost savings of AICD completions in six wells of more than $20 million in capital and operating expenses compared with a more conventional sliding side door completion to manage gas breakthrough.
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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.
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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…
