Abstract：Spectrum decomposition uses mathematical transformation to get tuning cube, time-frequency volume and single frequency volume (amplitude and phase) from seismic data. Maximum entropy method is applied in this article to calculate reservoir thickness, and the error is analyzed. At the same time the frequency scanning method is used to predict reservoir thickness and GST and RGB are used to predict sedimentary microfacies. First the log facies and sand body thickness are analyzed. Then the tuning amplitude of thin layer sandstones is used to determine reasonable tuning frequencies and analyze sand body thickness. Finally crossplots among response frequency, sand thickness, and sedimentary microfacies are built to predict the sedimentary microfacies under the restriction of well logging microfacies with logging-microfacies constrain. Application results confirm that the spectral decomposition combined with well data can intuitively reflect channel sand reservoir thickness and sedimentary microfacies belt distribution.
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