Pipe flow experiments of unstable oil-water dispersions with three different oil viscosities: Flow pattern, pressure drop and droplet size measurements

The transport of oil-water dispersions in petroleum production pipelines is difficult to predict and requires special attention since it affects the performance of the entire system. For future field developments it is required to generate accurate predictive models to guarantee an optimal field design. The purpose of this work is to present novel experimental data suitable for improving mechanistic flow models in future works. Oil-water pipe flow experiments were conducted in a stainless-steel flow loop with a L/D ratio of 3766, larger than any comparable setups reported in the literature and sufficient to obtain fully developed flow. A novel level of detail measurements included pressure gradients, density profiles and droplet size distributions. Three oils with different viscosities (oil A: 1.3 cP; oil B: 7 cP; oil C: 22 cP) and brine (3.5 wt% NaCl) as the water phase constituted the three fluid systems used. For each fluid system, several flow rates, and a wide range of water fractions were studied. The fluids were not stabilized by any type of chemical additives. The oil viscosity influences the dispersion behavior, especially for oil continuous flow. For higher oil viscosities the dispersion tends to be more homogeneous, and the pressure drop increases due to increasing wall friction. The droplet size decreases as the oil viscosity increases, presumably due to higher shear stress. Water continuous flows, on the other hand, are less affected by the oil viscosity. A strong drag reduction was found for dispersed flow of all three oils and both oil and water continuous flow. A simple model for the dispersion viscosity and drag reduction was developed based on additional bench scale characterization experiments. With this model the pressure drop could be predicted with good agreement. The data reported in this paper will facilitate the development and validation of mechanistic models for predicting oil-water flows. Previous modelling efforts have been hampered by a lack of detailed measurements, in particular droplet size measurements, hence we believe that this data will allow for significant advancements on the modelling side.