Abstract：It is difficult to extract accurate wavelets and build fine low-frequency models through well seismic calibration for hydrocarbon source rocks in few-well areas. Therefore, a prestack seismic inversion prediction method for hydrocarbon source rocks in few-well areas based on blind signal theory is proposed. First, according to the theory, the blind wavelets are extracted from the seismic data by higher-order statistics, and the low-frequency components of the model parameters are estimated in the complex frequency domain based on Bayesian theory. Then the blind wavelets and low-frequency model are further employed for elastic impedance inversion in the complex frequency domain. Finally, the relationship between the elastic impedance and physical parameters of hydrocarbon source rocks is established by the seismic petrophysics model of hydrocarbon source rocks. Physical parameters such as the shale content and indicator of hydrocarbon source rocks are obtained by elastic impedance inversion to predict the spatial distribution features of hydrocarbon source rocks in few-well areas and quantitatively evaluate hydrocarbon source rocks. In this method, the blind seismic wavelet extraction is a statistical method that does not require well data. The extracted blind seismic wavelet can provide priori constraints for the prestack seismic inversion of hydrocarbon source rocks in few-well areas. The proposed method solves the problem that deterministic wavelet extraction cannot be performed in the no-well or few-well areas. The reliability and accuracy of this method are proven by the test results.
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