小波分析在测井裂缝识别中的应用

针对井下裂缝发育层段识别的难点,提出了用小波分析的方法分解声波时差信号，使井下的岩性与微观结构特征信号、流体性质信号、裂缝响应信号和随机干扰信号互相分离，直接重构出反映裂缝发育的声波高频信号，从而避免许多声波低频信号的影响，正确识别裂缝发育情况。用同样的方法分解双侧向电阻率信号，重构出电阻率测井各个层段的低频信号，直观地反映深、浅侧向的差异情况，有效地识别裂缝发育层位。最后结合高频声波信号和低频电阻率信号，识别出裂缝发育层段。应用表明，该方法与岩芯观察有很好的一致性。

Application of Wavelet Analysis in Recognizing Fractures by Logging

Recognition of the fractures in the wells is a hard problem,the research submits the method of wavelet analysis to decompose the interval transit time information,which makes the microstructure characteristic signal,fluid characteristic signal,despondences of fractures and random disturbance signal separated from lithology,the high frequency signals reflecting fractures are directly reconstructed to avoid the influence of low frequency signal and recognize development of fractures correctly.Also,the same method is used to decompose the microelectrode log signals,reconstruct the low frequency signals that reflect the permeable layer.At last,combination of the high frequency signal of fractures and the low frequency signal of microelectrode log can help to recognize the layer of fracture development.Practice in oil gas field indicates the results from the method are consisting with the results coming from the core inspection.