Automated digital twin reduces pipeline monitoring cycle time by 98%, suggesting improved maintenance activities and data accuracy.
Objectives/Scope Pertamina Hulu Rokan (PHR) operates within a vast perimeter encompassing over 10,000 active wells distributed across an area of 6,200 square kilometers. To ensure efficient operations, PHR maintains an extensive network of pipelines spanning more than 13,200 kilometers, facilitating the transportation of over 9 million barrels of fluid daily. To enhance pipeline integrity monitoring and optimize maintenance activities, PHR has implemented an automated digital twin solution that has provided real-time insights and enabling proactive decision-making. Methods, Procedures, Process A digital twin is a virtual model that replicates a physical object or system. In this instance, it relies on pipeline geospatial data and advanced network simulation software. The digital twin solution for PHR involves automatic data integration and network auto-calibration process conducted daily, including the development of a smart monitoring system through an interactive dashboard. This dashboard utilizes software programming interface features and a meticulously designed matching algorithm to seamlessly connect the model and field measurement data. Furthermore, integration with pipeline integrity data enhances the capability to monitor pipeline operations while maintaining operational excellence in process safety. Results, Observations, Conclusions The project, initiated in early 2023, has been successfully implemented in key Rokan fields. The automated digital twin implementation has resulted in a remarkable 98% reduction in the data collection and pressure-matching process cycle time, facilitating task completion within a 2-hour timeframe, as opposed to the 5-day duration associated with the manual process. This innovative approach eliminates the potential for human errors, thereby enhancing work accuracy. The interactive dashboard provides a comprehensive overview of the actual field situation and offers valuable insights for the operation and maintenance team. These insights facilitate effective field intervention strategies, such as identifying areas with severe erosional risk and high operating pressure issues, enabling precise targeting for routine pipeline maintenance. The focus has shifted from data collection and pipeline modeling to strategic decision-making and future planning. The integration of pipeline geospatial data and automation algorithms into hydraulic simulation enhances PHR's operational efficiency and safety. It has resulted in significant cost savings of $590,000 year-to-date and an 81% reduction in field exposure, equivalent to 1,143 kilometers driven. This reduction has a positive impact on the environment, with a 0.21-ton reduction in CO2 emissions. Ultimately, the robust pipeline's integrity monitoring feature has prevented production losses due to pipe leaks, saving approximately 134 barrels of oil per day on an annualized basis. Novel/Additive Information This paper will provide a detailed explanation of how PHR's revolutionary digital twin of automated network simulation can significantly improve the cost-effectiveness of pipeline project and maintenance activities. This method has the potential to be applied in various locations and ultimately enhance operational excellence in process safety.
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Kayely et al. (2025) studied this question.
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