An Enhanced Model for the prediction of Minimum Transport Conditions in Multiphase Flow Systems

Abstract

Hydrocarbon production accompanied by the flow of sand from reservoirs is unavoidable as many of the formations are poorly consolidated. The deposition of the produced sand at low velocities or production of sand at very high velocity can pose serious challenges to the condition of the petroleum pipeline as it can lead to pipeline capacity reduction and degradation respectively. It is therefore important to investigate the minimum transport velocity that prevents sand deposition in the pipelines. In this study, the firefly optimization algorithm (FFA) was used in the development of the improved model for the prediction of minimum transport condition (MTC) in a multiphase pipeline. The model development was implemented using the MATLAB software package. The input parameters were sand concentration, particle diameter, viscosity, density and superficial velocity of the hydrocarbons. The developed model was observed to perform better than the base model with a R2 value of 0.9845 and 0.8149 for the developed model and base model respectively. The newly developed model was also compared with some existing models and the statistical measures show that the developed model gave a better performance. This enhanced model can be used for the prediction of MTC in multiphase pipelinesKeywords— Algorithms, Artificial Neural Network (ANN), Firefly algorithm (FFA), Minimum Transport Condition (MTC)