Applying a Smart Technique for Accurate Determination of Flowing Oil-Water Pressure Gradient in Horizontal Pipelines

Abstract

Two-phase flow of liquids in pipelines is crucial subject in many industries such as chemical and petroleum. Accurate prediction of pressure gradient will lead to a better design of an energy efficient transportation system. Although numerous studies for prediction of two-phase flowing pressure drop have been reported in the literature, the accurate prediction of this parameter has been a topic of debate in many research areas. In this article, a novel model based on least square support vector (LSSVM) was proposed for calculation of two-phase flowing pressure drop in horizontal pipes. The inputs of this model are oil and water superficial velocities, pipe diameter, pipe roughness, and oil viscosity. To develop and test the model, more than 700 experimental dataset from open literature were utilized. The results of proposed model were compared against the well-known empirical correlations. Statistical error analysis showed that the LSSVM model outperforms existing predictive models. Finally, an outlier diagnosis was performed to detect the doubtful experimental.