【摘要】 传统希尔伯特变换(Hilbert-Huang transform, HHT)是一种识别精度较差的时频分析方法，存在端点效应和模态混叠等问题。改进的完备经验模态分解(Improve Complete Ensemble Empirical Mode Docomposition, ICEEMD)可以将复杂的地震信号分解为一系列单分量信号，较好地解决模态混叠问题，但结合希尔伯特变换提取的瞬时振幅和瞬时频率，对处理实际地震数据仍然有严重的端点效应。FWEO(Frequency-weighted Energy Operator)是一种非负频率权重算子，其结合TK能量差分算法和Hirbert变换复分析思想，具有比Hilbert变换更高的时间分辨率。但由于算法本身的原因，FWEO能量只能应用于单分量信号，不能直接应用于复杂的地震数据。因此，这里结合改进的完备经验模态分解方法和FWEO能量分离算法的优点，提取南海某工区实际地震记录的瞬时振幅和频率信息，并将预测结果与测井数据对比，预测吻合程度好、识别精度高、证明该方法可以准确地反映储层特征。更多还原

【Abstract】 The traditional Hilbert-Huang transform(HHT) is a time-frequency analysis method with poor recognition accuracy and suffers from endpoint effects and modal aliasing. The improved Complete Empirical Mode Decomposition(ICEEMD) can decompose complex seismic signals into a series of single-component signals, which can better solve the problem of modal aliasing. However, the instantaneous amplitude and instantaneous frequency extracted by the combined Hilbert transform still have serious endpoint effects on the processing of real seismic data. FWEO(Frequency-weighted Energy Operator) is a non-negative frequency-weighted operator that combines TK energy difference algorithm and the Hilbert transform complex analysis idea, and has higher time resolution than the Hilbert transform. However, due to the algorithm itself, the FWEO energy can only be applied to single-component signals and not directly to complex seismic data. Therefore, this paper combines the advantages of the improved complete empirical mode decomposition method and FWEO energy separation algorithm to extract the instantaneous amplitude and frequency information of the actual seismic records in a work zone in the South China Sea and compares the prediction results with the logging data with good prediction agreement and high recognition accuracy, which proves that the method can accurately reflect the reservoir characteristics.更多还原