Optimizing Leak Detection and Flow Cessation Through Automated Transient Flow Simulation

Abstract Pipeline leaks pose serious operational and environmental risks in oil and gas infrastructure. Shutdowns triggered by such events can result in considerable production losses and ecosystem harm. This paper presents a simulation-based methodology for evaluating leak detection and flow cessation strategies using a dynamic transient multiphase flow model. The workflow includes the modeling of pipeline hydraulics, leak behavior, and a control logic that mimics the actions of Emergency Shutdown (ESD) systems within the simulation environment. A light black oil with zero gas-oil ratio (GOR = 0) was used to simulate pipeline conditions under various operating scenarios. The simulation began with the pipeline fully filled with water and progressed to a 50% oil-water mixture over a 48-hour transient run. A leak, defined by a 0.5-inch orifice located 100 meters from the inlet, was then introduced and analyzed over a 10-hour period. Simulated pressure and flow transmitters monitored key parameters and fed signals to virtual ESD controllers. These controllers, configured with threshold setpoints, were connected to an algebraic logic system that controlled the simulated closure of a downstream valve and stoppage of inlet flow when conditions deviated from safe limits. The simulation results captured dynamic responses to leak onset, including pressure decay and reduced outlet flow. Leak volume was estimated based on transient flow deviations. Once the threshold values were breached, the control logic successfully triggered simulated flow cessation, demonstrating the potential for automated leak response strategies to minimize environmental and operational impacts. This study offers a practical and scalable simulation framework for assessing pipeline integrity management strategies. By embedding virtual control logic directly into transient simulations, operators and engineers can evaluate the effectiveness of leak detection and response mechanisms before field implementation, reducing design uncertainty and improving system preparedness.