Data-Driven Performance Enhancement of Intelligent Injector Control System (IICS) in Oil and Gas Industry Using Six Sigma Framework

The oil and gas industry is essential to the global energy supply, with well stimulation via Coiled Tubing technology serving as a key method for enhancing production. Operational challenges, particularly pipeline damage, frequently result in substantial downtime, increased costs, and elevated safety risks. Analysis of historical data from 2019 to 2022 at a global energy service provider revealed a rising trend in failures, as pipe damage incidents increased from 15 to 22 per year and average downtime per incident rose from 8.05 to 11.05 hours. This study examines the deployment of an Intelligent Injector Control System (IICS) to optimize the stimulation process and elevate safety standards. The Six Sigma methodology, specifically the DMAIC (Define, Measure, Analyze, Improve, Control) framework, was applied to systematically assess and enhance system performance. IICS integration utilizes real-time data from smart sensors and automated control algorithms to enable proactive monitoring and intervention. Findings indicate that IICS implementation reduced pipe damage frequency from 20 to 10 incidents per year and decreased downtime from 11.5 to 6.5 hours per incident. Additionally, operational quality improved from 1.8 Sigma to 2.5 Sigma level, as confirmed by statistical control charts. The system facilitates real-time detection and automatic parameter adjustment, offering a robust, data-driven solution to complex industrial operational challenges.