The use of leak detection and location systems has became a common practice in the control rooms of pipeline operations, whereby operators are automatically alerted of a leak, and informed of its approximate location. Considerable attention has primarily been paid to leak sensitivity and leak detection time. However, this paper shows that in long pipelines the volume lost after a pipeline shutdown can be substantially more than what was lost prior to the detection. In very irregular altimetry, the drainage from the pipeline segment can represent a greater volume of spillage as compared to the spillage from the start of the leak until its detection. These volumes can be reduced by taking the appropriate actions. This work will illustrate the importance of having a leak contingency plan that orients the operators to take suitable actions that will diminish the volume spilled. A leak contingency plan is a detailed plan of recommended actions, for example valve closure and pumping shutdown, and the specific time sequence in which they have to be executed. The design of these plans was based on the use of hydraulic transient simulations of an actual 3000-km network in Argentina.

The use of statistical tools to improve the decision aspect of leak detection is becoming a common practice in the area of computer pipeline monitoring. Among these tools, the sequential probability ratio test is one of the most named techniques used by commercial leak detection systems [1]. This decision mechanism is based on the comparison of the estimated probabilities of leak or no leak observed from the pipeline data. This paper proposes a leak detection system that uses a simplified statistical model for the pipeline operation, allowing a simple implementation in the pipeline control system [2]. Applying linear regression to volume balance and average pipeline pressure signals, a statistically corrected volume balance signal with reduced variance is introduced. Its expected value is zero during normal operation whereas it equals the leak flow under a leak condition. Based on the corrected volume balance, differently configured sequential probability ratio tests (SPRT) to extend the dynamic range of detectable leak flow are presented. Simplified mathematical expressions are obtained for several system performance indices, such as spilled volume until detection, time to leak detection, minimum leak flow detected, etc. Theoretical results are compared with leak simulations on a real oil pipeline. A description of the system tested over a 500 km oil pipeline is included, showing some real data results.

A novel leak localization method for multi section pipelines is presented. Based on normal operation flowing thermodynamic pressure drop patterns along the pipeline, the system continuously compares with the measured pressure drops, and makes a decision based on the best fit finding the section where the leak occurs. A statistical approach is used accounting for noisy measured signals. The method uses steady state fluid equations, a recursive parameter estimation algorithm, and statistical decision and pattern recognition techniques. A modification is introduced to consider the cost of making a wrong leaky section choice in terms of the excess volume spilled due to gravitational flow after pipeline shut down. This leads to a Bayesian decision scheme minimizing a risk functional. The costs are the spill volumes, obtained from dynamical simulation of the pipeline, under the various possible decision scenarios. Finally, details are given of the successful implementation of the system on a 500km long oil pipeline, and real data from a simulated leak experiment are shown.