通过对测井信号离散小波多尺度的分解和重构，探讨了小波分析在测井层序划分中的适用性，并利用小波变换，选择合适的尺度因子进行了测井信号旋回界面的识别和地层层序的划分。根据小波变换的方法，对二连盆地白音查干凹陷达30井腾格尔组自然伽马（GR）测井信号进行了小波多尺度的分解和重构，形成了不同尺度的近似信号和细节信号，然后进行了不同层次旋回界面的识别和地层层序的划分研究。实例表明，小波的多尺度变换对多级别测井旋回层序的划分比较适用，可提高测井旋回层序划分的精度。

 The applicability of wavelet analysis to well logging sequence stratigraphic division was discussed through decomposing and reconstructing of log signals using scattered multi scale wavelets. Cycle surfaces and sequence stratigraphy were recognized and divided using wavelet transformation and by selection of suitable scale factors. According to the method of wavelet transformation, multiscaled wavelets were decomposed and reconstructed, and the approximate and detail signals were formed in different scales. The identification of different level cycles and and the division of sequence stratigraphy were carried out using the GR logging data of the Tengge’er formation in well Da 30 of the Baiyinchagan sag. The results indicate that multiscale wavelet transformation can enhance the precision of the division of logging cycle sequence stratigraphy boundaries