Reliability Enhancement of Electric Submersible Pumps in Oil Fields: A Comparative Study of Predictive and Reactive Maintenance Using Survival Analysis and Weibull Models

Khalili, Yasin; Ahmadi, Mohammad; Keshavarz Moraveji, Mostafa

doi:10.22050/ijogst.2026.561582.1763

Reliability Enhancement of Electric Submersible Pumps in Oil Fields: A Comparative Study of Predictive and Reactive Maintenance Using Survival Analysis and Weibull Models

Document Type : Research Paper

Authors

Yasin Khalili ¹

Mohammad Ahmadi ²

Mostafa Keshavarz Moraveji ³

¹ Department of Petroleum and Geoenergy Engineering, Amirkabir University of Technology, Tehran, Iran

² Department of Petroleum and Geoenergy Engineering, Amirkabir University of Technology, Tehran, Iran.

³ Department of Chemical Engineering, Amirkabir University of Technology, Tehran, Iran

https://doi.org/10.22050/ijogst.2026.561582.1763

Abstract

Electrical Submersible Pumps (ESPs) are widely used to sustain oil production in mature and challenging reservoirs; however, their frequent failures often lead to production deferment, costly workovers, and reduced operational efficiency. This study presents a comparative evaluation of predictive maintenance (PM) and reactive maintenance for ESP systems using 50 case studies from diverse reservoirs and operating conditions. Reliability performance was assessed using mean time between failures (MTBF), mean time to failure (MTTF), failure rate, Kaplan–Meier survival analysis, and Weibull probability modeling. The economic impact of maintenance strategy was also evaluated through failure-related costs and deferred production losses.

The results indicate that PM consistently enhances ESP reliability by extending operational run life and reducing failure occurrence. Median survival increased from approximately 400 days before PM implementation to about 750 days after PM adoption, while Weibull analysis showed a shift from early random failures toward more predictable wear-out behavior. Economic evaluation further demonstrated that PM reduces workover frequency and production-loss exposure, yielding estimated cost savings of approximately 30–40% across the analyzed cases, even after accounting for monitoring and diagnostic investments.

This study contributes to the ESP reliability literature by providing an integrated comparison of predictive and reactive maintenance using survival analysis, Weibull modeling, and economic assessment within a unified framework across multiple field cases. The findings confirm that predictive maintenance is both technically effective and economically justified, and they highlight the value of combining advanced monitoring, reliability analytics, and data-driven maintenance planning to improve ESP performance and reduce life-cycle costs in oilfield operations.

Highlights

· A comparative evaluation of predictive and reactive maintenance strategies was conducted for electric submersible pump (ESP) systems using 50 field case studies.

· Predictive maintenance significantly increased ESP run life, mean time between failures (MTBF), and survival probability across diverse operating conditions.

· Weibull and Kaplan–Meier models were applied to quantify failure behavior and improvements in post-maintenance reliability.

· An integrated reliability index combining MTBF, survival probability, and economic performance increased from 0.45 to 0.78 following the implementation of predictive maintenance (PM).

· Predictive maintenance reduced workover frequency, deferred production losses, and overall failure-related costs by approximately 30–40%.

· The study provides an integrated technical and economic framework for ESP reliability assessment and maintenance planning.

· The proposed workflow can be extended to other artificial lift systems in digital oilfield applications.

Keywords

Carbonate reservoir rock

enhanced oil recovery

low-salinity water polymer flooding

smart water polymer flooding

wettability

Subjects

Petroleum Engineering – Production

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