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通常情况下,不同地层特征对应的地震波复杂程度是有差异的。近似熵是一种反映信号复杂程度的特征量,对储层特征有一定反映。但由于地震波是有一定带宽的信号,波形受带宽内所有频率成分的影响,如果直接进行近似熵的计算,其结果往往不能很好地反映储层特征。鉴于这种情况,提出了经验模态分解法(EMD)与近似熵相结合的方法,利用EMD分解后的每一个地震波的本征模函数(IMF)分量进行近似熵计算,并与已知井对比分析后,选取对储层特征识别有效的IMF分量进行储层预测。利用该方法对HZ地区珠江组进行了试算,效果较好。
Under normal circumstances, the seismic wave characteristics corresponding to different stratigraphic differences are different. Approximate entropy is a feature quantity that reflects the complexity of the signal and reflects the reservoir characteristics. However, since the seismic wave is a signal with a certain bandwidth, the waveform is affected by all the frequency components within the bandwidth. If the approximate entropy calculation is performed directly, the results often do not reflect well the reservoir characteristics. In view of this situation, a new method combining EMD and approximate entropy is proposed. The approximate entropy is calculated by using the intrinsic mode function (IMF) component of each seismic wave after EMD decomposition, After comparative analysis, we choose the IMF component that is valid for reservoir character recognition for reservoir prediction. This method is used to test the Zhujiang Formation in HZ area, and the result is better.