Rejection of seamless pipe noise in magnetic flux leakage data obtained from gas pipeline inspection

Afzal, Muhammad; Udpa, Satish; Udpa, Lalita; Lord, William
May 2000
AIP Conference Proceedings;2000, Vol. 509 Issue 1, p1589
Academic Journal
Natural gas is traditionally transmitted from production facilities to customer locations through a vast pipeline network. A major segment of this network employs seamless pipes. This is especially true for smaller diameter transmission and distribution lines. Manufacturing process associated with the production of seamless pipes contribute to a helical variation in the pipe along the axis. The deformation introduces an artifact in the data obtained from MFL inspection of these pipelines. This seamless pipe noise is usually correlated with signals generated by defects and other elements (joints, tees, etc.) in pipelines, and can therefore, mask their indications in MFL data. This warrants the need for methods to improve signal-to-noise ratio (SNR) in MFL data from seamless pipes. This paper presents a technique for detecting signals in MFL data from seamless pipes. The approach processes the data in various steps. First, a wavelet based denoising technique is applied to reduce the noise due to instrumentation and other sources. An adaptive filtering approach is then applied to reject seamless noise in the data. Since the inspection of pipelines typically generates vast amounts of data, it is imperative that the algorithm be computationally efficient. The processing method has to be robust in that it should be data independent. The approach described in this paper meet these criteria. Results from application of the approach to data from field tests are presented. © 2000 American Institute of Physics.


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