Oilfield chemistry
This article is the second of a two-part series on produced-water management in the Gulf of Mexico and covers four themes: equipment, process configuration, operations, and effluent quality.
Field examples of operators using chemical restimulation to boost production in aging unconventional wells as an alternative to acid treatments.
This work investigates a cost-effective and sustainable alternative to acidification for sheen control.
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This study emphasizes the vital need to evaluate well conditions and working-fluid compatibility with coiled tubing materials to prolong coiled tubing operational life.
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Engineers desperately need an alternative to acid placement through pipe, coiled tubing, or bullheading. For example, propellants have been around for years; however, their performance has not quite met the hype. Nevertheless, several case histories have been authored to suggest their efficacy; historically, some treatments have even been wildly successful.
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The effects of aging and temperature on the performance of one-part “just add water” granite based geopolymers are studied for application in well cementing and abandonment. Further studied is the role of zinc as a strength enhancer over a long curing period.
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This paper presents the evaluation results of a water-shutoff agent based on an emulsion-type chemical material with nanoparticles.
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The authors of this paper discuss the use of dissolved polystyrene waste for the preparation of nanomembranes for separation of hydrocarbon pollutants from wastewater streams.
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The best wells in which to find lithium are in old conventional fields where rusty pump jacks are pulling out mostly water.
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A new study from Saudi Aramco shows that the answer to the industry's billion-dollar corrosion problem might be sitting in your medicine cabinet.
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Part 4 of this series provides an overview of ongoing research and recent technology improvements within the US taking place in both academia and the service industry.
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This paper sheds light on newer frontiers of tracer applications with unconventional uses to gain flow insights from an oil and gas reservoir.
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This paper presents a family of machine-learning-based reduced-order models trained on rigorous first-principle thermodynamic simulation results to extract physicochemical properties.