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The leakage of hydrocarbon products from a pipeline not only represents the loss of natural resources, but it also is a serious and dangerous environmental pollution and potential fire disaster. Quick awareness and accurate location of the leak event are important to reduce losses and avoid disaster. A leak-detection method using transient modeling is introduced in this paper. This method is suitable for both gas and liquid pipelines, with comprehensive consideration of the transient-flow features of compressible flows and stochastic processing and noise filtering of the meter readings. The correlations for diagnosing the leak location and amount are derived on the basis of the online real-time observation and the readings of pressure, temperature, and flow rate at both ends of the pipeline. As an online real-time system, great attention has been paid to the stochastic processing and noise filtering of the meter readings and the models to reduce the impact of signal noise. It is also essential for the robust realtime pipeline observer to have the self-study and adjustment abilities needed to respond to the large varieties of pipeline configuration, pipeline operation conditions, and fluid properties. Real application cases are presented here to demonstrate this leak-detection method. For example, in the leak detection of a crude-oil pipeline of 34.5 km long and 219 mm (nominal diameter), this method located the leak at 16.6 km from the pipeline upstream end, which is only 0.6 km away from the actual leak location.

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For new submarine hot oil pipelines, accurate simulation of preheating is difficult owing to complex transient flow and coupled heat transfer happening. Using quasi-steady equations to simulate preheating is inadequate as the hydraulic transient phenomenon is neglected. Considering this fact, this paper constructs an unsteady flow and heat transfer coupled mathematical model for the preheating process. By combining the double method of characteristics (DMOC) and finite element method (FEM), a numerical methodology is proposed, namely, DMOC-FEM. Its accuracy is validated by field data collected from the Bohai sea, China, showing the mean absolute percentage error (MAPE) of 4.27%. Simulation results demonstrate that the preheating medium mainly warms submarine pipe walls rather than the surrounding subsea mud. Furthermore, during the preheating process, the equivalent overall heat transfer coefficients deduced performs more applicably than the inverse-calculation method in presenting the unsteady propagation of fluid temperature with time and distance. Finally, according to the comparison results of 11 preheating plans, subject to a rated heat power and maximum flow, the preheating parameter at a lower fluid temperature combined with a higher flow rate will produce a better preheating effect.