Y. Baba, A. Aliyu, N. E. Okeke, A. S. Girei, H. Yeung
{"title":"Evaluating the Effects of High Viscosity Liquid on Two Phase Flow Slug Translational Velocity using Gamma Radiation Methods","authors":"Y. Baba, A. Aliyu, N. E. Okeke, A. S. Girei, H. Yeung","doi":"10.2118/198720-MS","DOIUrl":null,"url":null,"abstract":"\n Slug translational velocity, described as the velocity of slug units, is the summation of the maximum mixture velocity in the slug body and the drift velocity. Accurate estimation of this parameter is important for energy-efficient design of oil and gas pipelines. A survey of the literature revealed that existing prediction models of this parameter were developed based on observation from low viscosity liquids (of 1 Pa.s or less). However, its behaviour in pipes transporting higher viscosity oils is significantly different. In this research work, new data for slug translational velocity in high-viscosity oil-gas flows are reported. Scaled experiments were carried out using a mixture of air and Mineral oil of viscosity ranging from 0.7 to 6.0 Pa.s in a 17-m long horizontal pipe of 0.0762 m ID. Temperature dependence of the oil's viscosity is given as μ=−0.0043T3+0.0389T2−1.4174T+18.141. The slug translational velocity was measured by means two pairs of two fast-sampling Gamma Densitometers with a sampling frequency of 250 Hz. For the range of experimental flow conditions investigated, increase in liquid oil viscosity was observed to strongly influence slug translational velocity. A new predictive correlation incorporating the effect of viscosity on slug translational velocity was derived using the current dataset and incorporating those obtained in literature with oil viscosity ranging from 0.189–6.0 Pa.s for horizontal flow. A comparison by statistical analysis and validation and of the new closure relationship showed a remarkably improved performance over existing correlations.","PeriodicalId":11110,"journal":{"name":"Day 2 Tue, August 06, 2019","volume":"161 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 2 Tue, August 06, 2019","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/198720-MS","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Slug translational velocity, described as the velocity of slug units, is the summation of the maximum mixture velocity in the slug body and the drift velocity. Accurate estimation of this parameter is important for energy-efficient design of oil and gas pipelines. A survey of the literature revealed that existing prediction models of this parameter were developed based on observation from low viscosity liquids (of 1 Pa.s or less). However, its behaviour in pipes transporting higher viscosity oils is significantly different. In this research work, new data for slug translational velocity in high-viscosity oil-gas flows are reported. Scaled experiments were carried out using a mixture of air and Mineral oil of viscosity ranging from 0.7 to 6.0 Pa.s in a 17-m long horizontal pipe of 0.0762 m ID. Temperature dependence of the oil's viscosity is given as μ=−0.0043T3+0.0389T2−1.4174T+18.141. The slug translational velocity was measured by means two pairs of two fast-sampling Gamma Densitometers with a sampling frequency of 250 Hz. For the range of experimental flow conditions investigated, increase in liquid oil viscosity was observed to strongly influence slug translational velocity. A new predictive correlation incorporating the effect of viscosity on slug translational velocity was derived using the current dataset and incorporating those obtained in literature with oil viscosity ranging from 0.189–6.0 Pa.s for horizontal flow. A comparison by statistical analysis and validation and of the new closure relationship showed a remarkably improved performance over existing correlations.