EXPERIMENTAL ASSESSMENT OF PREDICTIVE WAX DEPOSITION MODELS IN SIMULATION SOFTWARE

One of the most relevant flow assurance issue in oil transportation is indeed the phenomena of wax deposition. Wax deposition occur when the temperature along the pipeline falls below a point where it is described as Wax Appearance Temperature(WAT) of the oil. The deposition may cause a lot of probl...

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Bibliographic Details
Main Author: ABD AZIZ, AHMAD EZAT ADHA
Format: Final Year Project
Language:English
Published: Universiti Teknologi PETRONAS 2013
Subjects:
Online Access:http://utpedia.utp.edu.my/10652/1/Final%20Report.pdf
http://utpedia.utp.edu.my/10652/
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Summary:One of the most relevant flow assurance issue in oil transportation is indeed the phenomena of wax deposition. Wax deposition occur when the temperature along the pipeline falls below a point where it is described as Wax Appearance Temperature(WAT) of the oil. The deposition may cause a lot of problems to the industry and definitely will involve expensive cause to overcome the problem. The main objective of this study is to compare wax deposition predicted by a simulation model to operational data. Literature reviews was conducted extensively in order to have a better understanding regarding the topic and developments regarding this topic in recent years. The objective and scope of studies is determined. A Gantt chart is also constructed to measure the progress of the project. Forecasted result and outcome from this project are informations to determine which wax deposition method in certain software are the most reliable on predicting wax deposition to be use in Petroleum industry. Prediction of wax deposition indeed help to minimize the cost of operating such equipment. The model used for the wax deposition simulations in this study is described below. The properties of the fluids used in the study are presented and discussed. Then the simulation results are presented and compared to the existing field experience data. Finally, some conclusion are drawn. This simulation will enable prediction of wax deposition such as its wax deposition rate and thickness of deposition. A main conclusion of this paper is that wax deposition under field condition is not as severe as predicted by the model. This information will be greatly appreciated since it can assess remediation or prevention strategies, such as, the models can be used to evaluate insulation effectiveness or to estimate pigging frequency.