Leak Detection for Gas and Liquid Pipelines by Online Modeling
- Shouxi Wang (Gas Liquids Engineering Ltd.) | John Joseph Carroll (Gas Liquids Engineering Ltd.)
- Document ID
- Society of Petroleum Engineers
- SPE Projects, Facilities & Construction
- Publication Date
- June 2007
- Document Type
- Journal Paper
- 1 - 9
- 2007. Society of Petroleum Engineers
- 5.4.2 Gas Injection Methods, 4.2 Pipelines, Flowlines and Risers, 4.2.2 Pipeline Transient Behavior, 4.6 Natural Gas, 6.1.5 Human Resources, Competence and Training, 4.4.2 SCADA, 4.4.4 Pipeline Leak Detection
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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 real-time 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 219mm in 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.
When 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 a 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 noise. To issue reliable and accurate alarms, great efforts have been paid to the stochastic processing, filtering the noise of the meter readings and the models and reducing the impact of signal noise.
Fig. 1 shows how this method works on the system control and data acquisition system (SCADA). An online real-time pipeline observer, which will always be leakage-free, is running and putting out 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 (Wang and Wang 1996,Wang 1998).
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 advantage of this method over the pressure-point-analysis method is that it continues detecting the leak during the entire time it exists. Therefore, this method has more opportunity to locate the leak accurately and issue the alarm reliably.
|File Size||1 MB||Number of Pages||9|
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