Pigging operation is primarily conducted for flow assurance and integrity of the pipeline. It will ensure maximum throughput and minimize internal pipeline wall corrosion by removing debris, asphaltene, sulfate reducing bacteria (SRB) and other impurities from the pipeline. Currently at PMO, pigging operation is conducted per time-based as required by pipeline's Corrosion Management Plan (CMP). The pigging frequency will be revised should there are changes to the amount of water holdup inside the pipeline. Since there is no reliable way to predict how much water holdup and heavies will deposit, pigging frequency can be optimized only by learning system behavior. Once the system behavior is better understood, the condition-based pigging frequency can be optimized.

Mathematical study utilizing numerical method analysis was performed by doing mass balance analysis of the recorded pipeline discharge and landing flowrate. Daily flowrate discrepancies between inlet and outlet flow were plotted. Cumulative flowrate discrepancies were calculated via a numerical method analysis technique. Data delay was also considered based on pig traveling time and/or fluid velocity in pipeline. Pipeline simulation model was developed using iCON with OLGAS 3Phase flow correlation to validate liquid hold up findings from numerical analysis. Other relevant parameters and profiles of the pipelines are also calculated such as pressure, temperature, velocity and flow regime. iCON is a steady state and dynamic simulation software widely used in PETRONAS with a variety of applications for upstream and downstream businesses.

The study has realized accurate approach to quantify the amount of liquid hold-up volume as well as other operating parameters such as velocity, pressure profile, flow regime and temperature to identify the pigging requirements for the pipelines for Tapis-P to TCOT pipeline. PMO pipeline engineer optimized pigging activities by switching from time-based to condition-based pigging. Several case studies were demonstrated in this paper to show that the modeling techniques applied matched liquid holdup accumulated at receiving terminal.

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