AMUSE算法在声波测井数据处理中的应用

传统的声波测井信号处理方法采用滤波器滤除干扰信号,不能有效滤除与测井信号处于同一频段内的干扰信号.本文针对测井信号和干扰信号由相互独立的信号源产生,并被声波测井仪器的多个接收器接收这一特点,采用一种独立变量分析方法,AMUSE算法对接收器的获取信号进行分解,提取测井信号的波形信息.并利用测井信号的能量远大于干扰信号的能量这一特点,对AMUSE算法进行改进,利用接收器获取信号的能量信息,得到测井信号的幅度估计.该算法实现了对测井信号波形和幅度的提取,可以有效的提高声波测井数据的准确度.

Using AMUSE Algorithm in Acoustic Logging Wave Processing

Conventionally,filters were applied to eliminate the interferential acoustic signal in acoustic signal processing.However, the interferential signal with the same frequency as the acoustic logging signal can not be filtered. Considering that the logging signal and the interferential signal are generated by independent sources, and received by different receivers,an independent component analysis algorithm named AMUSE was applied to separate the logging signal and the interferential signal from the receiver signals. Also, considering that the energy of the logging signal is much bigger than that of the interferential signal, the energy of the receiver signals were used to estimate the amplitude of the acoustic logging signal. Thus the acoustic logging signal could be estimated both in waveform and amplitude, and the accuracy of the acoustic logging data would be improved.