One commonly used method for determining oil and gas production velocities is to limit production rates based on the American Petroleum Institute Recommended Practice 14E (API RP 14E). This guideline contains an equation to calculate an “erosional” or a threshold velocity, presumably a flow velocity that is safe to operate. The equation only considers one factor, the density of the medium, and does not consider many other factors that can contribute to erosion in multiphase flow pipelines. Thus, factors such as fluid properties, flow geometry, type of metal, sand production rate and size distribution, and flow composition are not accounted for. In the present paper, a method is presented that has been developed with the goal of improving the procedure by accounting for many of the physical variables including fluid properties, sand production rate and size, and flowstream composition that affect sand erosion. The results from the model are compared with several experimental results provided in the literature. Additionally, the method is applied to calculate threshold flowstream velocities for sand erosion and the results are compared with API RP 14E. The results indicate that the form of the equation that is provided by the API RP 14E is not suitable for predicting a production flowstream velocity when sand is present. [S0195-0738(00)00203-X]
Skip Nav Destination
e-mail: brenton-mclaury@utulsa.edu
e-mail: siamack-shirazi@utulsa.edu
Article navigation
September 2000
Technical Papers
An Alternate Method to API RP 14E for Predicting Solids Erosion in Multiphase Flow
Brenton S. McLaury,
e-mail: brenton-mclaury@utulsa.edu
Brenton S. McLaury
Department of Mechanical Engineering, The University of Tulsa, 600 South College Avenue, Tulsa, OK 74104-3189
Search for other works by this author on:
Siamack A. Shirazi
e-mail: siamack-shirazi@utulsa.edu
Siamack A. Shirazi
Department of Mechanical Engineering, The University of Tulsa, 600 South College Avenue, Tulsa, OK 74104-3189
Search for other works by this author on:
Brenton S. McLaury
Department of Mechanical Engineering, The University of Tulsa, 600 South College Avenue, Tulsa, OK 74104-3189
e-mail: brenton-mclaury@utulsa.edu
Siamack A. Shirazi
Department of Mechanical Engineering, The University of Tulsa, 600 South College Avenue, Tulsa, OK 74104-3189
e-mail: siamack-shirazi@utulsa.edu
Contributed by the Petroleum Division and presented at the ETCE/OMAE2000, New Orleans, Louisiana, February 14–17, 2000, of THE AMERICAN SOCIETY OF MECHANICAL ENGINEERS. Manuscript received by the Petroleum Division, October 28, 1999; revised manuscript received May 24, 2000. Associate Technical Editor: W. P. Jepson.
J. Energy Resour. Technol. Sep 2000, 122(3): 115-122 (8 pages)
Published Online: May 24, 2000
Article history
Received:
October 28, 1999
Revised:
May 24, 2000
Citation
McLaury, B. S., and Shirazi, S. A. (May 24, 2000). "An Alternate Method to API RP 14E for Predicting Solids Erosion in Multiphase Flow ." ASME. J. Energy Resour. Technol. September 2000; 122(3): 115–122. https://doi.org/10.1115/1.1288209
Download citation file:
Get Email Alerts
Related Articles
Distribution of Sand Particles in Horizontal and Vertical Annular Multiphase Flow in Pipes and the Effects on Sand Erosion
J. Energy Resour. Technol (June,2011)
A Comprehensive Procedure to Estimate Erosion in Elbows for Gas/Liquid/Sand Multiphase Flow
J. Energy Resour. Technol (March,2006)
Prediction of Solid Particle Erosive Wear of Elbows in Multiphase Annular Flow-Model Development and Experimental Validations
J. Energy Resour. Technol (June,2008)
An Alternative to API 14E Erosional Velocity Limits for Sand-Laden Fluids
J. Energy Resour. Technol (June,2000)
Related Proceedings Papers
Related Chapters
Multiphase Flow Simulations of Sediment Particles in Mixed-flow Pumps
Mixed-flow Pumps: Modeling, Simulation, and Measurements
Adaptive Grayscale Morphological Operators for Image Analysis
Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17
Application of Adaptive Grayscale Morphological Operators for Image Analysis
Intelligent Engineering Systems through Artificial Neural Networks Volume 18