Field-Validated Models for Predicting Electric Submersible Pump Run Life in Saudi Fields

Abstract

Abstract Although reliability analysis has been used for many years in different industries, the more rigorous analyses are relatively new applications in oil fields. Reliability analysis is using statistical analysis for analyzing the expected duration of time until one or more events happen. This technique is best applied in areas with single variable or changing parameter like corrosion rate. ESPs are engineered electromechanical systems having multiple components and materials. Very often, in ESP system, of multiple components and different quality; parametric analysis may not be applicable. This is due to the fact that the efficiency of an electric submersible pump system is function of the multiplied efficiencies of its components, i.e. motor, pump, seal, cable, etc. and hence this is still an area of debate in oil industry. Hence, censoring and data scrutiny, with projection of operational knowledge, would add more sense to the collected data. The use of reliability analysis for the estimation of run life of electrical submersible pump (ESP) has been sparsely applied in the oil field to predict the availability of a mechanical system such ESP. This is of a paramount importance to predict failure and plan for the availability of workover rig to replace ESP's. This paper present the results of a comparative statistical analysis applied to evaluate the run lives of electric submersible pumps in some Saudi fields using different reliability methods. This was carried out after data scrutinizing and screening to help analyze pump performance and optimize future installations. ESP design system was used to screen out improperly designed applications. The objective of this study was to investigate the use of statistical analyses in ESP run life calculation, identity what distribution functions best model ESP failure, estimate ESPs' run lives, identify potential improvement in ESP run life (inherent reliability vs. practical), estimate ESP replacement requirements, and compare results with ESP failure reports to explain changes in ESP life's.