Prediction of slug length for high-viscosity oil in gas/liquid horizontal and slightly inclined pipe flows

被引:2
|
作者
Shaaban, Omar M. [1 ]
Al-Safran, Eissa M. [1 ]
机构
[1] Kuwait Univ, Petr Engn, Kuwait, Kuwait
来源
关键词
Slug length; High viscosity; Mechanistic; Multiphase flow; Closure relationship; LIQUID HOLDUP; 2-PHASE FLOW; MECHANISTIC MODEL; INTERMITTENT FLOW; VOID FRACTION; LONG BUBBLES; FREQUENCY; VELOCITY; DRIFT; MOTION;
D O I
10.1016/j.geoen.2022.211348
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The production and transportation of high viscosity liquid/gas two-phase Newtonian mixtures along petroleum production systems is a challenging operation due to the lack of understanding the flow behavior and charac-teristics. In particular, accurate prediction of two-phase slug length in pipes is crucial to efficiently operate and safely design oil well and separation facilities. The objective of this study is to develop a mechanistic model to predict high viscosity liquid slug length in pipelines and to optimize the proper set of closure relationships required to ensure high accuracy prediction. A large high viscosity liquid slug length database is collected and presented in this study, against which the proposed model is validated and compared with other models. A mechanistic slug length model is derived based on the first principles of mass and momentum balances over a two-phase slug unit, which requires a set of closure relationships of other slug characteristics. To select the proper set of closure relationships, a numerical optimization is carried out using a large slug length dataset to minimize the prediction error. Thousands of combinations of various slug flow closure relationships were evaluated to identify the most appropriate relationships for the proposed slug length model under high viscosity slug length condition. Results show that the proposed slug length mechanistic model is applicable for a wide range of liquid viscosities and is sensitive to the selected closure relationships. Results revealed that the optimum closure relationships combination is Archibong-Eso et al. (2018) for slug frequency, Wong (2003) for slug liquid holdup, Jeyachandra et al. (2012) for drift velocity, and Nicklin et al. (1962) for the distribution coefficient. Using the above set of closure relationships, model validation yields 34% absolute average percent error, out-performing all existing slug length models.
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页数:11
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