The wavelet transform (WT) method has been employed to decompose an original geophysical signal into a series of components containing different information about reservoir features such as pore fluids, lithology, and pore structure. We have developed a new method based on WT energy spectra analysis, by which the signal component reflecting the reservoir fluid property is extracted. We have successfully processed real log data from an oil field in central China using this method. The results of the reservoir fluid identification agree with the results of well tests.%利用小波变换方法可以把原始信号分解为一系列载有不同信息的子信号,每种子信号载有储层的特定信息,包括流体、岩性和孔隙结构等.我们开发出了基于小波变换的谱分析方法,利用该方法可以从这些子信号中提取出反映地层流体特性的子信号,通过对该子信号的处理识别出地层所含流体的特性.本文利用该流体识别新方法对某油田的实际测井资料进行了处理,处理结果与试油结果符合得很好,进一步证明了本方法的可靠性和实用性.
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机译：The wavelet transform (WT) method has been employed to decompose an original geophysical signal into a series of components containing different information about reservoir features such as pore fluids, lithology, and pore structure. We have developed a new method based on WT energy spectra analysis, by which the signal component reflecting the reservoir fluid property is extracted. We have successfully processed real log data from an oil field in central China using this method. The results of the reservoir fluid identification agree with the results of well tests.%利用小波变换方法可以把原始信号分解为一系列载有不同信息的子信号,每种子信号载有储层的特定信息,包括流体、岩性和孔隙结构等.我们开发出了基于小波变换的谱分析方法,利用该方法可以从这些子信号中提取出反映地层流体特性的子信号,通过对该子信号的处理识别出地层所含流体的特性.本文利用该流体识别新方法对某油田的实际测井资料进行了处理,处理结果与试油结果符合得很好,进一步证明了本方法的可靠性和实用性.
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