Abstract
In oil and gas production, the operating conditions can be erosive when sand is entrained in the fluid. Sudden contraction and expansion geometries are commonly found in wellbores. Erosion prediction for these geometries is a challenging task since there is a relatively complex flow field with high turbulent kinetic energy and recirculation zones developed and the entrained particles are relatively small which can be easily affected by the flow field. Commercially available CFD codes provide a way to predict erosion for these geometries. This approach is able to predict the erosion trend but can severely over-predict the magnitude of erosion. Zhang et al.1 proposed a 2-D particle tracking method for predicting erosion for direct impingement and standard elbow geometries. With consideration of turbulence, this method performs very well for these two geometries regardless of sand size. This present work extends and improves this 2-D method to sudden contractions and expansions by incorporating more physics into the particle tracking model especially for the near wall treatment. A two-layer particle-turbulence interaction model is implemented. The turbulent core region applies a classical eddy interaction model, while the near wall region, an equivalent eddy scale is estimated to consider near wall turbulence. Results from a commercially available CFD code and the improved method are compared with experimental data. It is shown that for liquid/solid flows, the improved method performs very well in predicting erosion magnitude for sudden contraction and expansion geometries.
Introduction
Erosion calculation in many wellbore and valve geometries such as sudden contractions and expansions is a challenging task for the complex flow field developed and small particles (< 50 µm) entrained in the fluid. The flow field contains regions of high turbulent kinetic energy and recirculation, and small particles can be easily affected and driven by turbulence to impact the wall causing significant amount of erosion. Thus, in order to assess the integrity risk for process components in these erosive conditions, an accurate and reliable erosion prediction tool is essential and must be developed. Over the years, erosion prediction models have been developed by many investigators; however, many of these models are empirical with the physics lost in the modelling which limits their application.
