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Issue:ISSN 1006-5539
          CN 51-1183/TE

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    Your Position :Home->Past Journals Catalog->2021 Vol.5

    Wax deposition evaluation scheme for JF crude oil pipeline in Northwest China
    Author of the article:ZHANG Jianchang1, WANG Litao1, ZHOU Xiaoyu1, ZHANG Jiaan1, ZHANG Ni1, YU Dan1, DING Ni2
    Author's Workplace:1. The Third Oil Transportation Department of PetroChina Changqing Oilfield Company, Yinchuan, Ningxia, 750000, China; 2. PipePlus Technology Ltd., Xian, Shaanxi, 710065, China
    Key Words:Oil pipeline; Wax deposition; Equivalent thickness; Prediction model
    Abstract:

     In order to grasp the situation of wax deposition in oil pipelines on site, a field pipeline wax deposition evaluation method is proposed based on the analysis on large amount of operating data collected by the SCADA system. A kinetic wax deposition prediction model is established as well. Firstly, the equivalent wax deposition thickness was calculated by analyzing the changing characteristics of operating conditions and using the differential pressure profile method. Secondly, the effects of oil flow, average temperature and pipeline buried temperature on the equivalent wax deposition thickness are analyzed. Finally, a kinetic model of wax deposition was established to predict the variation in thickness of wax deposition. The calculation results were consistent with the results of 9 pigging operations for the JF crude oil pipeline, which proved the accuracy of the calculation results. The results show that, although the equivalent wax deposition thickness calculated by differential pressure method is not exactly the true wax deposition thickness, it can be used as an indicator to evaluate the wax deposition in pipeline as it reflects the influence of wax deposition on the hydraulic characteristics of pipeline. Since the wax deposition process is affected by both molecular diffusion and shear peeling, the HSU model has a better prediction effect. The maximum error of the prediction model is 1.74 mm/d. Among the 712 groups of data calculated, up to 72.9 % or 518 groups of data calculated results predicted the same trend with the actual change. The evaluation index proposed in this study can provide engineering reference, yet it should focus on promoting calculation precision and model adaptability and relying on network emulation technology to deepen the study.

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