Leak Detection for Gas and Liquid Pipelines by Transient Modeling (2006)

Leak Detection for Gas and Liquid Pipelines by Transient Modeling Shouxi Wang; Shouxi Wang Gas Liquids Engineering Ltd. Search for other works by this author on: This Site Google Scholar John Joseph Carroll John Joseph Carroll Gas Liquids Engineering Search for other works by this author on: This Site Google Scholar Paper presented at the International Oil & Gas Conference and Exhibition in China, Beijing, China, December 2006. Paper Number: SPE-104133-MS https://doi.org/10.2118/104133-MS Published: December 05 2006 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Wang, Shouxi, and John Joseph Carroll. "Leak Detection for Gas and Liquid Pipelines by Transient Modeling." Paper presented at the International Oil & Gas Conference and Exhibition in China, Beijing, China, December 2006. doi: https://doi.org/10.2118/104133-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE International Oil and Gas Conference and Exhibition in China Search Advanced Search AbstractThe leakage of hydrocarbon products from a pipeline represents not only the loss of natural resources, but also is a serious and dangerous environment pollution and potential fire disaster. So quick awareness and accurately location of the leak event are important to cut down the losses and avoid the disasters.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 based on 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 efforts have 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 essential too for the robust real time pipeline observer to have the self study and adjustment abilities in response 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 and F219mm, 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.IntroductionWhen there is a leak in the pipeline, the event will transfer to both upstream and downstream along the pipeline at the acoustic velocities. As a result the measurements at the pipeline ends will change. The different location and rate of the leak will result in different meter readings at the pipeline ends. This is why the pipeline internal thermodynamic flowing features can be used to identify the appearance of leak and determine its location.It is essential for a leak detection method and system to be sensitive to a small leak and insensitive to the system and measurement noises. In order to issue reliable and accurate alarms, great efforts have been paid to the stochastic processing, filtering the noises of the meter readings and the models, and reducing the impact of signal noises.Figure 1Fig. 1 shows how this method works on the SCADA based data acquisition system. A online real-time pipeline observer, which will always be leakage free, is running and outputting the expected readings for the pipeline without leakage, such as flow rates at the pipeline ends, according to the measured inputs, such as pressures and temperatures measured at the upstream and downstream ends. When there is a leakage, the observer outputs are different from the meter readings and the discrepancies between the observer outputs and the meter measurements can be used to identify the appearance, rate and location of the leak[2, 3].Because the leak detection of this method is based on the comprehensive internal flow features of the pipeline, it can be applied to the pipeline without concern for the upstream and downstream connections. The advantages of this method over the Pressure Point Analysis (PPA) method is that it continues detecting the leak during the entire time it exists. Keywords: climate change, real time system, measurement and control, discrepancy, pipeline observer, pipeline leak detection, air emission, flow rate, Artificial Intelligence, Midstream Oil & Gas Subjects: Pipelines, Flowlines and Risers, Measurement and Control, Environment, Pipeline leak detection, Air emissions, Oil and chemical spills, Climate change This content is only available via PDF. 2006. 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