The noise included in pipeline pressure signal is a small noise whose energy takes a small proportion of pressure signal and is concentrated on high frequency components. However, it will influence pipeline leakage identification and even cause false alarms. Thus, a small-noise reduction method based on EMD (SNR-EMD) is proposed to remove small noise from pressure signal. EMD is applied for extracting the mean envelope of the signal. Then, small fluctuations around the mean envelope are considered to be small noises. Meanwhile, end effect of SNR-EMD is restrained by extrema mirror extension (EME). The results of simulation studies with SNR-EMD show that the larger the noisy signal's signal-to-noise ratio (SNR) is, the better noise reduction effect becomes. And SNR-EMD considered as a low-pass filter removes or reduces the high frequency components. Furthermore, superiorities of SNR-EMD are verified by comparison studies with wavelet packet transform (WPT) and singular value decomposition (SVD). Finally, a case study of leakage identification shows that SNR-EMD can improve the performance of leakage identification and reduce the possibility of false alarms, which makes much easier and further effective to distinguish the leakage mode from other modes after removing noise from pressure signal. (C) 2016 Elsevier Ltd. All rights reserved.