Providing a Novel Semi-empirical Relationship for the Design of Two-phase Separators

Document Type : Research Paper

Authors

Petroleum Engineering Department, Amirkabir University of Technology, Tehran, Iran

Abstract

Separators play a very important and key role in oil and gas production fields. For this reason, their optimal design is very important. The design method with semi-empirical equations is a common method for determining the dimensions of separators. However, due to the simplifying assumptions used in them, it can only be used to obtain an approximate estimate of the dimensions of the separators. In this study, the accuracy of semi-empirical relationships was investigated using a gas-liquid separator pilot unit and the experimental results and the results obtained from CFD simulation as necessary data for the design and construction of a neural network optimized by Genetic algorithm. A model was proposed to determine the correction factor of semi-experimental relationships under different operating conditions. The pilot unit of the separator test consists of a laboratory-scale two-phase horizontal separator, pumps, compressors and a static mixer to form a two-phase flow and a liquid filter to trap liquid droplets from the exhaust gas flow from the separator. The separation efficiency is determined by weighing the dispersed liquid droplets. The maximum diameter of the liquid droplets in the exhaust gas flow is determined by imaging. The CFD model developed with laboratory data had a relative error of less than 8 percent, and the root mean square error of the neural network optimized by the genetic algorithm for the actual and predicted values of the correction factor was 1%. One of the most important achievements of this research is to provide the necessary basis for the optimal design of surface separators.
 

Keywords

References

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Journal of Petroleum Research
Volume 31, 1400-3 - Serial Number 118
September and October 2021
Pages 71-89

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