The reliable predictions of liquid holdup and pressure drop are essential for pipeline design in oil and gas industry. In this study, the drift-flux approach is utilized to calculate liquid holdups. This approach has been widely used in formulation of the basic equations for multiphase flow in pipelines. Most of the drift-flux models have been developed on an empirical basis from the experimental data. Even though, previous studies showed that these models can be applied to different flow pattern and pipe inclination, when the distribution parameter is flow pattern dependent. They are limited to a set of fluid properties, pipe geometries and operational conditions. The objective of this study is to develop a new drift-flux closure relationship for prediction of liquid holdups in pipes that can be easily applied to a wide range of flow conditions. The developed correlation is compared with nine available correlations from literatures, and validated using the TUFFP (Fluid Flow Projects of University of Tulsa) experimental datasets and OLGA (OiL and GAs simulator supplied by SPTgroup) steady-state synthetic data generated by OLGA Multiphase Toolkit. The developed correlation performs better in predicting liquid holdups than the available correlations for a wide range of flow conditions.

Summary: Droplet formation in oil/water flow through a centrifugal pump has been studied, experimentally and theoretically, for the first time. Droplet-size distribution at the pump outlet has been measured for water-continuous flow as a function of pump speed, mixture-flow rate, and water cut. The measured droplet-size distribution strongly depends on the pump speed: the higher the pump speed, the smaller the droplet size. Negligible effects of mixture-flow rate, water cut, and inlet droplet-size distribution have been observed. Turbulent breakup has been identified as the main mechanism for droplet formation. A mechanistic model is developed for the prediction of droplet-size distribution in a centrifugal pump, showing a fair agreement with the acquired experimental data.