Summary
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.
Introduction
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.
© 2007. Society of Petroleum Engineers
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History
- Original manuscript received:
16 September 2006
- Meeting paper published:
5 December 2006
- Revised manuscript received:
30 January 2007
- Manuscript approved:
1 March 2007
- Version of record:
20 June 2007
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