A transient analysis of slug flow in a horizontal pipe using slug tracking model: Void and pressure wave. (April 2022) - Gonçalves, Jéssica Leonel; Mazza, Ricardo Augusto
Highlights: Influence of a transient phenomenon in properties such as void fraction and pressure. Definition of the time scale for the damping between two steady states. Dependence decrease of experimental data in transient simulations. Slug tracking model is used to assess the steady-state slug flow parameters. Numerical results demonstrate a good agreement with experimental data. Abstract: In the oil and gas industry, the transient flow arises in daily situations, such as the start-up and shutdown of lines, pigging, artificial lifting, and drilling operations. These disturbances affect the temporal behavior of pressure and void fraction, which could cause separator flooding, system vibration, and production line facilities damage. Nevertheless, there are few numerical studies to describe this phenomenon. In this article, the transient slug flow is studied using the slug tracking model, which predicts the transient behavior and the evolution of slug flow properties. This study demonstrates the slug tracking model's capability to reproduce the transient flow as well as the pressure and void fraction wave's behavior and velocity. Experimental data presented by Maria and Rosa, 2016 were used to assess the model performance. The experimental data show a 6.0 s time delay between the two steady states. This time delay does not influence the void fraction wave, and its numerical maximum deviation is 9.0%. On the other hand, the numerical performance for the pressure wave velocity depends on the time delay. Using the experimental time delay, the maximum deviation for the pressure wave velocity is 6.8%. The slug tracking model is combined with a mass–dashpot–spring analogy to avoid the experimental time delay dependency. Using this methodology, the maximum deviation for pressure wave velocity is 8.2%. Some slug flow properties, such as the bubble nose translational velocity, the bubble and liquid slug lengths, are also compared to experimental data. The comparison is for averaged values and statistical distribution. The bubble nose velocities and pressure deviations are less than 1.5%, while the bubble and liquid slug lengths deviations are 4.1% and 5.3%, respectively. Most slug flow parameters have normal statistical distribution, but slug length follows a close to log-normal distribution. The model reproduces this behavior.