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大规模盆地测试模拟海底溢油情况下的油滴实际分布以及海底分散剂注入的影响。

Large-scale basin testing to simulate realistic oil droplet distributions from subsea release of oil and the effect of subsea dispersant injection.

机构信息

SINTEF Ocean, Marine Environmental Technology, Trondheim, Norway.

SINTEF Ocean, Marine Environmental Technology, Trondheim, Norway.

出版信息

Mar Pollut Bull. 2021 Feb;163:111934. doi: 10.1016/j.marpolbul.2020.111934. Epub 2021 Jan 4.

Abstract

Small-scale experiments performed at SINTEF, Norway in 2011-12 led to the development of a modified Weber scaling algorithm. The algorithm predicts initial oil droplet sizes (d) from a subsea oil and gas blowout. It was quickly implemented in a high number of operational oil spill models used to predict fate and effect of subsea oil releases both in academia and in the oil industry. This paper presents experimental data from large-scale experiments generating oil droplet data in a more realistic multi-millimeter size range for a subsea blow-out. This new data shows a very high correlation with predictions from the modified Weber scaling algorithm both for untreated oil and oil treated by dispersant injection. This finding is opposed to earlier studies predicting significantly smaller droplets, using a similar approach for estimating droplet sizes, but with calibration coefficients that we mean are not representative of the turbulence present in such releases.

摘要

2011-2012 年,挪威 SINTEF 进行的小规模实验导致了改良 Weber 比例算法的开发。该算法可预测海底油气井喷初始油滴尺寸(d)。该算法迅速在大量用于预测海底溢油事故命运和影响的作业溢油模型中得到实施,这些模型在学术界和石油行业都有应用。本文介绍了在更大规模的实验中获得的实验数据,这些实验在更接近实际的多毫米尺寸范围内生成了油滴数据,用于海底井喷。新数据显示,无论是未经处理的油还是经分散剂注入处理的油,与改良 Weber 比例算法的预测结果都具有非常高的相关性。这一发现与之前的研究结果相反,此前的研究使用类似的方法估算油滴尺寸,但使用的校准系数并不代表此类溢油中存在的湍流。

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