In oil and gas production, annular flow is a common flow regime found in wells and pipelines. Predicting erosion in multiphase flow is a challenging task as so many factors and phase interactions are involved. Computational Fluid Dynamics (CFD) offers a way to predict multiphase flow erosion. This present work shows how this state-of-the-art erosion model is applied to a 3 inch elbow to calculate erosion under annular flow conditions and how an improved 2-D model is developed for calculating erosion in annular flow for elbow geometries. The CFD predicted results are compared with experimental data and good agreement is observed. Flow solution from CFD and collected erosion data are also utilized to improve a 2-D model for annular flow application. It is shown that the combined CFD and 2-D model is a promising erosion prediction procedure for annular flows.


Predicting solid particle erosion in multiphase flow is difficult as so many factors are involved in the problem. Currently, both experimental and numerical approaches can be applied to investigate the phenomenon of multiphase flow erosion. Several experimental studies were conducted at the University of Tulsa Erosion/Corrosion Research Center (E/CRC) to measure erosion in multiphase flow (Dosila, 2008; Vieira, 2015; Parsi; 2015; Fan, 2010). However, there are still many questions unanswered and especially modelling of multiphase flow erosion has not been extensively studied. This is especially the case for annular flow commonly found in oil and gas production.

Dosila (2008) found through experimentation that for annular flow the erosion rate can decrease when liquid flow rate increases above a critical value.2 Fan (2010) also observed the same behavior even for large pipe diameters.3 Vieira (2015) studied the effect of elbow orientation on erosion in annular flow. He found that erosion in a vertical-horizontal elbow was significantly higher than that in a horizontal-horizontal elbow. He improved a 1-D simplified model by increasing the initial particle tracking velocity. The factor was obtained empirically through flow experimental data4.

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