Closed-Loop ESP Optimization to Maximize Asset Value

Electric Submersible Pumps (ESPs) play a crucial role in enhancing oil recovery, particularly in unconventional fields where reservoir conditions pose significant challenges. The primary objective of this study is to explore the implementation of a closed-loop optimization system for ESPs, aiming to improve operational efficiency and reliability. By integrating high frequency measurement data, advanced analytics, and automated control mechanisms, the closed-loop system continuously monitors and adjusts ESP performance to adapt to dynamic reservoir conditions. This approach not only maximizes production rates but also extends the lifespan of the equipment, thereby reducing operational costs and minimizing downtime. The scope of this research encompasses the development and validation of the closed-loop system through field trials, highlighting its potential to revolutionize ESP operations in unconventional oil fields. The closed-loop ESP optimization system begins by integrating recommendations from a commercial software designed for single well optimization using physics-based models. These recommendations are generated based on real-time data and advanced analytics to enhance the performance of individual wells. Once the recommendations are received, a series of internal system checks are conducted to ensure their feasibility and safety. These checks verify that the proposed adjustments comply with operational constraints and safety protocols, such as facility constraints, ESP operational parameters, etc., preventing any adverse effects on the production process. Upon successful validation, the approved recommendations are transmitted to field devices for execution. This automated process ensures that the ESPs operate at optimal efficiency, adapting dynamically to changing reservoir conditions while maintaining production within safe and predefined limits. The closed-loop optimization system was piloted on 26 ESP wells in our Midland assets. Initial tests have confirmed the successful integration of the full data pipeline with field devices from various controller types and manufacturers. Recommendations that passed all the system checks can be automatically written to the devices with no human interactions. This deployment has demonstrated several key benefits: it significantly reduces the time required to execute optimization changes and troubleshoot issues, thereby minimizing the chase for sub-optimal volumes. The system ensures production adheres to constraints immediately after wells are put on production, both at the facility and ESP levels. Additionally, it reduces the manhours spent on surveillance and optimization (S&O) and change execution, allowing personnel to focus on higher-value initiatives such as artificial lift system (ALS) design, inflow optimization, and complex troubleshooting. Furthermore, the closed-loop system is easily scalable across assets, maintaining consistency in execution and enhancing overall operational efficiency. Preliminary results from our ongoing pilot are used to offer early insights into the effectiveness of our optimization approach. This study introduces a novel closed-loop system for ESP optimization, leveraging real-time data and automated control to enhance performance and safety. The integration of commercial software with robust validation processes sets a new standard for operational efficiency. The successful pilot across diverse field devices demonstrates the system's scalability and versatility, significantly reducing optimization time and manpower while enabling strategic initiatives.