Array Acoustic Logging Signal Analysis And Fluid Identification Method

Array sonic logging use multiple receiver, that would constitute an array receiver. which can effectively suppress noise. It may improve the accuracy of data processing.This paper is according to the characteristics of array sonic log record format. We developed a format conversion software. This software can compiled array acoustic logging documents to normal text files. After this we analyzed and summarized monopole and dipole array acoustic waveform data under the different strata.The impact of noise on waveform is evident by using array sonic logging. For completion of post-processing of the waveform, we must use noise reduction. This paper firstly analysis the waveform by using the fast fourier transform approach. Then we comparison the differences between the performance characteristics of filters. Finally this paper applied the wave filter by using Chebyshev filters. The fourier transform simplely converts a signal to the frequency domain. But wavelet theory can see the signal by multiple layers of decomposition. Therefore this paper used wavelet theory to reduce noise. Finally summed up the array acoustic waveform denoising features.The key to array sonic logging processing is accurately calculated the slowness of P&S wave and ST wave. This paper used STC theory to calculate the slowness of P&S wave and ST wave.Gassmann first proposed calculate elastic modulus formula in porous rock filled with fluid. This formula laid the basis for elasticity theory and the physical properties of sediment. This paper used Gassmann theory to deduce new method for fluid identification. It has a better perform in field. This theory can effectively identify the thin reservoir by Comparing to other methods.