The filtering characteristics of HHT and its application in acoustic log waveform signal processing

Array acoustic logging plays an important role in formation evaluation. Its data is a non-linear and non-stationary signal and array acoustic logging signals have time-varying spectrum characteristics. Traditional filtering methods are inadequate. We introduce a Hilbert-Huang transform (HHT) which makes full preservation of the non-linear and non-stationary characteristics and has great advantages in the acoustic signal filtering. Using the empirical mode decomposition (EMD) method, the acoustic log waveforms can be decomposed into a finite and often small number of intrinsic mode functions (IMF). The results of applying HHT to real array acoustic logging signal filtering and de-noising are presented to illustrate the efficiency and power of this new method.

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