Currently, it is difficult for people to express signal information simultaneously in the time and frequency domains when analyzing acoustic logging signals using a simple-time or frequency-domain method. It is difficult to use a single type of time-frequency analysis method, which affects the feasibility of acoustic logging signal analysis. In order to solve these problems, in this paper, a fractional Fourier transform and smooth pseudo Wigner Ville distribution （SPWD） were combined and used to analyze array acoustic logging signals. The time-frequency distribution of signals with the variation of orders of fractional Fourier transform was obtained, and the characteristics of the time-frequency distribution of different reservoirs under different orders were summarized. Because of the rotational characteristics of the fractional Fourier transform, the rotation speed of the cross terms was faster than those of primary waves, shear waves, Stoneley waves, and pseudo Rayleigh waves. By choosing different orders for different reservoirs according to the actual circumstances, the cross terms were separated from the four kinds of waves. In this manner, we could extract reservoir information by studying the characteristics of partial waves. Actual logging data showed that the method outlined in this paper greatly weakened cross-term interference and enhanced the ability to identify partial wave signals.
During surveys, water layers may interfere with the detection of oil layers. In order to distinguish between oil and water layers in a porous cracked medium, research on the properties of cracks and oil and water layers and their relation to acoustic logging rules is essential. On the basis of Hudson＇s crack theory, we simulated oil and water layers in crack-porous medium with different crack parameters corresponding to the well-field response. We found that in a cracked medium with high crack angle or low number density of cracks, compressional and shear wave velocities are sensitive to crack characteristics; further, these velocities are more sensitive to crack characteristics when the waves propagate through the water layer than when they propagate through the oil layer. Compressional and shear wave velocities increase with an increase in crack angle： in the water layer, the increase is approximately linear. On comparing the full waveforms observed in the oil and water layers, we find that the amplitudes of most waves are higher in the water layer. Among the considered waves, the Stoneley wave suffers maximum amplitude attenuation in the oil layer. The maximum excitation intensity for oil layer is greater than that for the water layer. These results can guide further cracked media logging field exploration work.
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.
