Evaluating Electrical Submersible Pumps (ESPs) [SS1] [NA2] run-lives and performance in unconventional well environments is challenging due to many different factors -including the reservoir, well design, and production fluids. Moreover, reviewing the run-lives of ESPs in a field can be rather complex since the run-life data is incomplete. Often ESPs are pulled while they are still operational, or the ESP has not been allowed to run until failure. These are some of the complications that arise when gauging ESP performance.
A large dataset of ESP installs was assessed using Kaplan-Meier survival analysis for the North American unconventional application to better understand those factors that may affect ESP run lives. The factors were studied including but are not limited to the following:
Basin and producing formation
Comparing different ESP component types such pumps and motors, and new or used ESP components
Completion intensity of the frac job (lb/ft of proppant)
Kaplan-Meier survival analysis is one of the commonly used methods to measure the fraction or probability of group survival after certain time periods because it accounts for incomplete observations. Using Kaplan-Meier analysis generates a survival curve to show a declining fraction of surviving ESPs over time. Survival curves can be compared by segmenting the runlife data into buckets (based on different factors), therefore to analyze the statistical significance of each and how they affect ESP survivability.
Kaplan-Meier analysis was performed on the aforementioned dataset to answer these questions in order to better understand the factors that affect ESP runlives in North American unconventional plays.
This work uses a unique dataset that encompasses several different ESP designs, with the ESPs installed in different North American plays. The observations and conclusions drawn from it, by applying survival analysis, can help in benchmarking ESP runtimes and identifying what works in terms of prolonging ESP runlife. The workflow is also applicable to any asset in order to better understand the drivers behind ESP runlife performance.