基于湍流附加应力的减阻率预测模型

1. 中石油管道有限责任公司西部分公司;2. 西安西北石油管道有限公司;3. 西安石油大学石油工程学院

混合长度理论;湍流;预测模型;管径修正;黏度修正

A prediction model of drag reduction rate based on turbulent additional stress
JIANG Yuyou1, XIE Jin2, WANG Shouxi3, SHI Ying3, QIU Shujuan1, LI Jian1, FENG Jun1, CHEN Jingyu1

1. PetroChina West Pipeline Company; 2. Xi'an Northwest Oil Pipeline Co. Ltd.; 3. College of Petroleum Engineering, Xi'an Shiyou University

mixing length theory, turbulence, prediction model, pipe diameter correction, viscosity correction

DOI: 10.6047/j.issn.1000-8241.2019.12.007

备注

目前,越来越多的管道采用加减阻剂运行的方式,采用减阻率预测模型指导现场加剂运行,可以避免造成浪费。通过分析加剂前后摩阻因数与湍流附加应力的关系,结合混合长度理论中对湍流附加应力的求解方法,以及减阻率负指数单因素经验方程,建立了减阻率预测模型;针对贝克休斯 FLO_MXA、康菲 Liquid Power TM、ks-30-01 油气集输以及甲种减阻剂,利用大量现场加剂运行数据,确定模型中的递减率和流动特性系数,并对同一种减阻剂应用于不同管道进行管径和黏度的修正,得到修正系数。验证表明:修正后预测模型对于不同减阻剂、不同管道均可进行预测,且预测精度高,预测结果的相对误差保持在10%以内,最小误差可接近0。(图4表2,参[20]

At present, more and more pipelines adopt the operation mode of adding drag reduction agent (DRA). A good prediction model of drag reduction rate can provide the guidance for on-site operation of adding DRA and avoid unnecessary waste. In this paper, a prediction model of drag reduction rate was established based on the method in the mixing length theory for solving the turbulence additional stress and the single-factor empirical equation of the negative index of drag reduction rate, after the relationships between the friction coefficient and turbulence additional stress before and after the DRA addition were analyzed. Then, for FLO MXA of Baker Hughes, Liquid Power TM of ConocoPhillips, ks-30-01 and JIA Species DRA, the decline rate and flow characteristic coefficient in the model were determined using a large number of onsite operation data. In addition, the same DRA was applied to different pipelines for pipe diameter and viscosity correction, and accordingly the correction coefficient was obtained. It is indicated that the proposed prediction model can be used for the prediction of different pipes and different DRAs, and the prediction accuracy is high. The relative error of the prediction results remains within 10% and the minimum valve can be as low as zero. (4 Figures, 2 Tables, 20 References)

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