A Generic Model for Optimizing the Selection of Artifical Lift Methods for Liquid Loaded Gas Wells

Rehman, A., Soponsakulkaew, N., Bello, O. O. and Falcone, G. (2011) A Generic Model for Optimizing the Selection of Artifical Lift Methods for Liquid Loaded Gas Wells. In: SPE Annual Technical Conference and Exhibition, Denver, Colorado, 30 Oct-2 Nov 2011, (doi: 10.2118/146606-MS)

Abstract

An increasing number of gas wells worldwide produce at rates below their maximum potential due to liquid loading, which occurs when the gas velocity in the well falls below a critical value, at which point the liquid that was previously carried upward by the gas begins to fall back. The liquid accumulates down hole, where it increases the hydrostatic back-pressure on the reservoir, destabilizes the multiphase flow in the well, decreases gas production rate, in severe cases, can kill the well. There are a number of tools, techniques and processes that are currently used in the industry to mitigate the impact of liquid loading. Choosing the optimum artificial lift solution for a specific occurrence of loading in the field is a very challenging task that requires an integrated, multi-disciplinary approach to deliver the highest possible value for the asset. The objective of this paper is to develop a quantitative method which couples integrated production simulations, economic analysis and a distance-based optimization model to streamline and improve the selection of the most appropriate lifting option for given well conditions, while considering multiple factors impacting on the decision making process. The production system is modeled with a widely available commercial software package. The feasibility of using integrated production modeling in conjunction with a distance-based optimization methodology is demonstrated with two synthetic case studies representing a high-rate and a low-rate gas well. The results show that the proposed methodology can help optimize the selection of artificial lift solutions for liquid loaded gas wells.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Falcone, Professor Gioia
• Authors: Rehman, A., Soponsakulkaew, N., Bello, O. O., and Falcone, G.
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy