399656 The Effect of Computational Fluid Dynamics Methodology on Solid Particle Erosion Predictions

Monday, April 27, 2015: 2:30 PM
12A (Austin Convention Center)
Deval Pandya1,2, Ronnie Russell3 and Brian Dennis1, (1)The University of Texas at Arlington, Arlington, TX, (2)Shell Global Solutions, Houston, TX, (3)Baker Hughes, Houston, TX

Solid particle erosion is one of the major factors affecting the longevity, reliability and safety of downhole tools. Thus, it is of great interest to accurately predict flow-induced erosion caused by low particle loading (up to 10%). Computational fluid dynamics (CFD) has emerged as a powerful and cost-effective tool to predict erosion in tools involving complex flow regimes. Significant successful efforts have been made to accurately predict erosion regions; however, some CFD-based erosion models have poor performance in quantitative predictions. In some cases, the error is as high as an order of magnitude.  

In this work, a finite-volume based software ANSYS Fluent was employed as a tool to develop CFD-erosion model. CFD-based erosion predictions consists of three major steps, fluid flow and turbulence modeling to simulate flow behavior, discrete particle modeling to predict solid particle trajectory in the flow and application of empirical models to predict erosion as a post processing step.  The empirical models are based on CFD-output parameters like flow velocity, particle concentration, particle volume fraction, etc. CFD modeling strategy has had a great impact on accurate erosion predictions using empirical models. This study investigates the effect of CFD modeling parameters like numerical schemes, turbulence models, near-wall treatment, grid strategy and discrete particle model parameters. The results are evaluated for a benchmark case of a flow through elbow with different particle sizes and flow rate. A new modified model to predict erosion is proposed. A novel computational approach that improves quantitative accuracy of erosion models is presented. This can significantly contribute in improving reliability and safety by providing guidelines for design, repair and maintenance of downhole tools.


Pandya, D., Dennis, B. and Russell, R. 2014. An Improved Computational Fluid Dynamics (CFD) Model for Erosion Prediction in Oil and Gas Industry Applications. Presented at the ASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering -San Francisco, California. http://dx.doi.org/10.1115/OMAE2014-23136

Russell, R. and Marsis, E. 2013. A State-of-the-Art Computational Fluid Dynamics Simulation for Erosion Rates Prediction in a Bottom Hole Electrical Submersible Pump. Presented at the SPE Heavy Oil Conference-Canada. Calgary, Alberta, 11-13 June.  SPE-165452-MS http://dx.doi.org/10.2118/165452-MS

Extended Abstract: File Uploaded