DATA ANALYTICS CASE STUDY IN OPTIMIZING WELL WORKOVER PROCESS

This study focuses on optimizing well workover processes in the oil and gas industry using advanced data analytics and digital tools. Data collected from the OIS Well Workover IT solution is analyzed with Python to enhance efficiency, reduce costs, and improve decision making during workover operations. By examining planning, execution, and monitoring phases, the research identifies inefficiencies and proposes automation strategies to streamline processes. Actionable recommendations are provided to address operational challenges and enhance data quality, contributing to cost savings and optimized production. This work establishes a foundation for future research on leveraging digital solutions to promote innovation and efficiency in the oil and gas industry.