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.
本文就星形树与m-C4并图的优美性进行探讨,证明了当m≥2这类图Stp∪m-C4是优美图.并对星形树St与∪from i=1 to n mi-C4并图St∪from i=1 to n mi-C4的优美性进行探讨.证明了当maxmi≥3 i=1,2,...,n这类图St∪from i=1 to n mi-C4是优美图.
