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Role of Shearing Dispersion and Stripping in Wax Deposition in Crude Oil Pipelines

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  • Zhihua Wang

    (Key Laboratory for Enhanced Oil & Gas Recovery of the Ministry of Education, Northeast Petroleum University, Daqing 163318, China
    Heilongjiang Key Laboratory of Petroleum and Petrochemical Multiphase Treatment and Pollution Prevention, Daqing 163318, China)

  • Yunfei Xu

    (Key Laboratory for Enhanced Oil & Gas Recovery of the Ministry of Education, Northeast Petroleum University, Daqing 163318, China)

  • Yi Zhao

    (Research Institute of Petroleum Engineering and Technology, Sinopec Northwest Oilfield Company, Urumqi 830011, China)

  • Zhimin Li

    (Research Institute of Petroleum Engineering and Technology, Sinopec Northwest Oilfield Company, Urumqi 830011, China)

  • Yang Liu

    (Key Laboratory for Enhanced Oil & Gas Recovery of the Ministry of Education, Northeast Petroleum University, Daqing 163318, China)

  • Jiajun Hong

    (Key Laboratory for Enhanced Oil & Gas Recovery of the Ministry of Education, Northeast Petroleum University, Daqing 163318, China)

Abstract

Wax deposition during crude oil transmission can cause a series of negative effects and lead to problems associated with pipeline safety. A considerable number of previous works have investigated the wax deposition mechanism, inhibition technology, and remediation methods. However, studies on the shearing mechanism of wax deposition have focused largely on the characterization of this phenomena. The role of the shearing mechanism on wax deposition has not been completely clarified. This mechanism can be divided into the shearing dispersion effect caused by radial migration of wax particles and the shearing stripping effect caused by hydrodynamic scouring. From the perspective of energy analysis, a novel wax deposition model was proposed that considered the flow parameters of waxy crude oil in pipelines instead of its rheological parameters. Considering the two effects of shearing dispersion and shearing stripping coexist, with either one of them being the dominant mechanism, a shearing dispersion flux model and a shearing stripping model were established. Furthermore, a quantitative method to distinguish between the roles of shearing dispersion and shearing stripping in wax deposition was developed. The results indicated that the shearing mechanism can contribute an average of approximately 10% and a maximum of nearly 30% to the wax deposition process. With an increase in the oil flow rate, the effect of the shearing mechanism on wax deposition is enhanced, and its contribution was demonstrated to be negative; shear stripping was observed to be the dominant mechanism. A critical flow rate was observed when the dominant effect changes. When the oil flow rate is lower than the critical flow rate, the shearing dispersion effect is the dominant effect; its contribution rate increases with an increase in the oil flow temperature. When the oil flow rate is higher than the critical flow rate, the shearing stripping effect is the dominant effect; its contribution rate increases with an increase in the oil flow temperature. This understanding can be used to design operational parameters of the actual crude oil pipelines and address the potential flow assurance problems. The results of this study are of great significance for understanding the wax deposition theory of crude oil and accelerating the development of petroleum industry pipelines.

Suggested Citation

  • Zhihua Wang & Yunfei Xu & Yi Zhao & Zhimin Li & Yang Liu & Jiajun Hong, 2019. "Role of Shearing Dispersion and Stripping in Wax Deposition in Crude Oil Pipelines," Energies, MDPI, vol. 12(22), pages 1-19, November.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:22:p:4325-:d:286467
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    References listed on IDEAS

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    1. Leporini, Mariella & Marchetti, Barbara & Corvaro, Francesco & Polonara, Fabio, 2019. "Reconversion of offshore oil and gas platforms into renewable energy sites production: Assessment of different scenarios," Renewable Energy, Elsevier, vol. 135(C), pages 1121-1132.
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    1. Girma Tadesse Chala & Berihun Mamo Negash, 2022. "Artificial Neural Network and Regression Models for Predicting Intrusion of Non-Reacting Gases into Production Pipelines," Energies, MDPI, vol. 15(5), pages 1-14, February.

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