傅里叶变换和小波变换在同位素能谱测井数据处理中的应用

Application of data processing based on fourier transform and wavelet transform in isotope spectrum logging

同位素注入剖面能谱测井采集到的同位素能谱存在较大统计涨落,影响测井资料的解释精度。文章介绍了常用的两种信号处理方法——傅里叶变换与小波变换的基本原理,针对同位素注入剖面能谱测井得到的131Ba能谱,分别采用傅里叶变换与小波变换进行了降噪处理,并对两种方法的降噪效果进行了对比。对比结果显示,基于小波变换的降噪方法与传统的傅里叶变换方法相比,降噪效果更好,能谱重建质量更高。现场试验结果证明,同位素能谱经过小波变换处理后,具有比傅里叶变换更好的纵向分辨率。

The interpretation accuracy is affected by big statistical fluctuation of the isotope spectrum logging. The basic principles of Fourier transform and Wavelet transform are introduced, the de-noising processing is implemented on the131 Ba spectrum by the two methods mentioned above. The de-noising effects of the two methods are compared and the result shows that the Wavelet transform has the better noise reduction and spectrum retrieve quality than the traditional Fourier transform method. In addition, field test results proved that the axial resolution of isotope spectrum treated by Wavelet transform is better comparing with the Fourier transform.