摘要
给出小波波谱分方法析及其快速算法 ,该方法保留了波谱的位置信息 ,使我们了解在序列中存在的周期特征、位置和信号的迭加模式等 .开发了该方法的WINDOWS应用程序 ,并用此程序计算了新疆塔里木盆地X11井 15 0 0～ 2 5 0 0m段RILD ,GR ,SP ,DEN测井曲线的周期图与小波波谱 .在小波波谱中发现了清晰的构造沉降和水平面变化—沉积物供应变化模式 .而用以往的周期图方法无法得到这些信息 .
Time series analysis method is important in well logging sequence analysis, paleoclimate research (such as Milankovitch cycles study), whilst the methods of cycles, successions, and rhythms methods are the most important. The wavelet scalogram which we presented here with fast calculation methods is better selection than the generally used cycles analysis methods such as auto-correlate power spectra methods, periodgram methods, MEM, MLM, and etc. Wavelet scalogram keeps the position information whereas we can not only find which frequency component is significant but also position where is that frequency, and more what the frequency stacking pattern is. A windows package is developed using widely the dynamic linked library (DLL) and Component Object Model (COM). Well logging curves, RILD, GR, SP, Den, of hole X11 from 1500m to 2500m in Tarim basin, XinJiang Chig are used to calculate periodgram and wavelet scalogram as examples. The cycles peaks in periodgram contain less information than scalogram. The subsidence, eustatic, and flux patterns are clear in the scalogram images. The scalogram method is useful and efficient in cycles analysis.
出处
《地球物理学进展》
CSCD
2002年第1期78-83,101,共7页
Progress in Geophysics
基金
国家自然科学基金项目 (D497742 37)
