Ahmed Algarhy, Midland College
Omar Abdelkerim, and BJ Ellis, Liftrock Integrated Lift Services
Compressor downtime remains one of the primary causes of lost production, unstable injection performance, and fugitive methane emissions in gas lift operations. This paper reviews a zero-methane emission compression optimization system designed to stabilize gas lift performance by mitigating gas lift compressor issues, reducing shutdown frequency, and capturing methane emissions. The closed-loop system incorporates autonomous recirculation, real-time pressure control, and high-resolution monitoring to maintain steady gas-injection conditions and prevent scrubber-related malfunctions that commonly lead to compressor failures.
A large-scale field study was conducted across 77 gas compressors supporting 281 gas-lifted wells in the Permian Basin to evaluate the impact of deploying this optimization technology. The study compares compressor performance with and without the optimization skid in operation. Key performance indicators included shutdown frequency, downtime duration, under-injection events, scrubber liquid-level freeze-up incidents, methanol consumption associated with freeze-up mitigation, and methane emissions generated during disruption periods.
Results show that deploying the optimization system reduces compressor downtime by up to 90% compared with traditional mitigation methods by improving liquid handling and preventing liquid-level and dump-valve freeze-ups caused by the Joule–Thomson cooling effect under high differential pressure. These improvements result in a more stable and consistent gas-injection process. Operators reported a substantial decline in shutdown events and improved production consistency, leading to increased oil output and higher cash flow. Field data also confirmed complete methane capture during gas compression, including emissions from rod-packing vents and blowdowns, providing a clear environmental advantage in gas-lift operations.
Overall, the compression optimization system offers a practical and scalable solution for operators seeking to reduce downtime, lower operational costs, maximize oil production, improve gas-lift stability, and meet evolving environmental expectations. This field study provides a framework for integrating an automated optimization skid into field development strategies as operators target both operational reliability and environmental compliance.