Leak detection in petroleum pipelines using a fuzzy system

Leak detection in petroleum pipelines using a fuzzy system

Fuzzy systems

Pattern recognition

Pipeline leakage detection

A methodology for pipeline leakage detection using a combination of clustering and classification tools for fault detection is presented here. A fuzzy system is used to classify the running mode and identify the operational and process transients. The relationship between these transients and the mass balance deviation are discussed. This strategy allows for better identification of the leakage because the thresholds are adjusted by the fuzzy system as a function of the running mode and the classified transient level. The fuzzy system is initially off-line trained with a modified data set including simulated leakages. The methodology is applied to a small-scale LPG pipeline monitoring case where portability, robustness and reliability are amongst the most important criteria for the detection system. The results are very encouraging with relatively low levels of false alarms, obtaining increased leakage detection with low computational costs.

223-238

3

49

da Silva, Henrique V.

Morooka, Celso K.

Guilherme, Ivan R.

da Fonseca, Tiago C.

Mendes, José R.P.

An Introduction to Artificial Intelligence Applications in Petroleum Exploration and Production

2005

journalArticle

0920-4105

10.1016/j.petrol.2005.05.004

https://www.sciencedirect.com/science/article/pii/S0920410505001439