Fluid Mechanics and Transport Phenomena
A fundamental model of wax deposition in subsea oil pipelines
Article first published online: 15 FEB 2011
DOI: 10.1002/aic.12517
Copyright © 2011 American Institute of Chemical Engineers (AIChE)
Additional Information
How to Cite
Huang, Z., Lee, H. S., Senra, M. and Scott Fogler, H. (2011), A fundamental model of wax deposition in subsea oil pipelines. AIChE J., 57: 2955–2964. doi: 10.1002/aic.12517
Publication History
- Issue published online: 10 OCT 2011
- Article first published online: 15 FEB 2011
- Accepted manuscript online: 13 DEC 2010 03:03PM EST
- Manuscript Revised: 7 DEC 2010
- Manuscript Received: 28 MAY 2010
Funded by
- University of Michigan Industrial Affiliates Program: Chevron Corporation, ConocoPhillips Company
- Multiphase Solutions Inc
- Nalco Company
- Shell Global Solutions
- Schlumberger Limited
- Statoil ASA
- Total S.A.
- Abstract
- Article
- References
- Cited By
Keywords:
- petroleum;
- diffusion (mass transfer;
- heat transfer);
- wax deposition;
- modeling
Abstract
Wax deposition in subsea pipelines is a significant economic issue in the petroleum industry. A mathematical model has been developed to predict the increase in both the deposit thickness and the wax fraction of the deposit using a fundamental analysis of the heat and mass transfer for laminar and turbulent flow conditions. It was found that the precipitation of wax in the oil is a competing phenomenon with deposition. Two existing approaches consider either no precipitation (the independent heat and mass transfer model) or instantaneous precipitation (the solubility model) and result in either an overprediction or an underprediction of deposit thickness. By accounting for the kinetics of wax precipitation of wax in the oil (the kinetic model), accurate predictions for wax deposition for both lab-scale and pilot-scale flow-loop experiments with three different oils were achieved. Furthermore, this kinetic model for wax precipitation in the oil was used to compare field-scale deposition predictions for different oils. © 2011 American Institute of Chemical Engineers AIChE J, 2011

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