【摘要】 小波分析有“数学显微镜”之称,具有多分辨率的特点。实践证明,Mexican Hat小波函数在用连续小波变换将测井资料转换为小波系数,不同小波尺度对测井信号进行多分辨率处理方面比其它小波函数要好。由于小波系数与储层有很好的相关性:大尺度系数对应厚层的响应,小尺度系数对应薄层的响应,在实际应用中小波尺度以从大到小的方式进行取值,这样用小波系数对储层进行识别和划分,能够取得很好的效果。通过柴达木盆地跃进地区多口井的实际应用和对比,该方法在储层划分,特别是在薄层和薄互层的识别与划分方面具有迅速、准确的优点。同时对GR资料和SP资料的小波系数划分储层进行对比分析,表明GR资料具有不易错划储层和漏划储层的优点。更多还原

【Abstract】 The wavelet analysis has a name of "math-ematic microscope", being of a multi-resolution feature. It was proved in practice that the Mexican Hat wavelet function is better than the other wavelet functions in converting log data into wavelet coefficients by continuous wavelet transform and in multi-resolution processing of logging signals by different wavelet scales. The wavelet coefficient is well correlated to the reservoir, the big scale coefficient being corresponding to the response of thick layer and the small scale one to that of thin layer. In actual application, the selection of wavelet scales should follow the principle from big scale to small scale, by which a good result can be obtained in identifying and dividing reservoirs by wavelet coefficients. Through actually applying to several wells at Yuejin region in Chaidamu Basin and contrasting their results, it was indicated that such a method is of the advantages as high-speed, accuracy and so on in identifying and dividing reservoirs, especially in identifying and dividing thin layers and thin inter-beds. Meanwhile, by means of contrasting and analyzing the results of dividing reservoirs by the wavelet coefficients of GR and SP data, it was shown that the GR data have the advantage of being not easy to make a mistake in dividing reservoirs .更多还原