The Analysis and Prediction of Electric Submersible Pump Failures in the Milne Point Field, Alaska

Abstract

Summary Electric submersible pumps (ESPs) are the predominant lift method used in the Milne Point field, Alaska. Each year, approximately 50 ESP failures occur, adversely affecting lifting costs, rig utility, and production. Statistical methods based on the Weibull distribution and the bathtub reliability model have been used to analyze ESP reliability data collected over a 13-year period. This analysis differs from earlier works by treating a portion of the infant failures (the early part of the bathtub model) as a series of Bernoulli trials. Analysis shows that the three main factors affecting ESP reliability in the Milne Point field are reservoir, sand control, and whether the ESP is the first installed in a well or is a replacement. Further, the ESP failure rate is shown to be dynamic, influenced by the delivery of new wells and the time lag between failure and replacement. The results have been incorporated into a computer-based failure simulator that uses Monte Carlo techniques to simulate the failure rates. Numerical values for the statistical parameters are included with the details of the simulator. The simulator is currently used within the Milne Point field asset as a planning tool to establish changes in rig utility, production loss, and ESP replacement strategies in a cash-constrained environment. It is also used to assess improvements in ESP performance and to secure commercial terms for ESP lease and purchase options. In the future, it is recommended that the simulator be used, with suitable analog data, to predict the economic impacts of ESP failures on development programs before sanction.