Wear | 2021

A mechanistic model for predicting erosion in churn flow

 
 

Abstract


Abstract Sand particles, which are regularly entrained with the production fluids while transporting from a reservoir to surface facilities, can cause severe erosion and erosion-corrosion damage to production equipment. A crucial parameter for studying erosion in multiphase flows is the flow pattern. The particle motion characteristics will change drastically with changes in the flow pattern in the pipelines. In vertical upward gas-liquid flow, a widely accepted flow pattern classification is bubble, slug, churn and annular flow. Churn flow is a chaotic flow pattern consisting of Taylor bubbles and liquid slugs that are distorted in shape and it is characterized by the presence of periodic large interfacial waves called flooding-type waves. Studying the erosion due to sand particles entrained in churn flows is extremely difficult, since the solid particle erosion magnitudes are coupled with several multiphase flow parameters such as phase distribution and velocities. This work focuses on improvement of a multiphase churn flow erosion model for elbows in vertical pipes. In this investigation, a drift-flux model is proposed to better predict the flow behavior and the characteristic initial particle velocity for churn gas-liquid flow. Based on the drift-flux model, the actual gas velocity is calculated as a function of mixture and drift velocities. The coefficients of the drift flux expression under churn flow conditions are determined from datasets available in literature. The model predictions are compared with the erosion data bank at the Erosion/Corrosion Research Center and other published papers. The data comprises effects of pipe diameter, particle characteristics, flow velocities, and liquid viscosity. The results show that the new approach provides much better predictions for the maximum erosion in bends when compared with the original mixture based model and other models available in literature.

Volume None
Pages None
DOI 10.1016/J.WEAR.2021.203654
Language English
Journal Wear

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