Abstract：The strong reflection separation method based on matching pursuit algorithm has achieved good results in practical applications with different strong reflection types in recent years. However, the key algorithm parameter selection lacks a theoretical basis and standards with less research involved. Therefore, the meanings of the two key parameters of wavelet phase and separation coefficient are clarified during the strong reflection separation procedure in thin coal seams, and the parameter optimization method of strong reflection separation in thin coal seams based on matching pursuit algorithm is proposed, so as to further improve the characterization accuracy of strong reflection in thin coal seams and better carry out strong reflection separation, as well as reservoir prediction. Firstly, this paper classifies the strong reflection wavelet characteristics according to different types of strong reflection reservoirs and analyzes the phase feature of strong reflection in thin coal seams. Then, based on the reflection coefficient calculation and separation of the practical drilling well, the paper determines the energy relationship between strong and weak reflections and estimates the separation coefficient to improve the separation result of strong reflection. The application result shows that this method can accurately identify strong reflection features in thin coal seams and significantly improve separation results. It highlights the weak reflection characteristics of the reservoir and lays a solid data foundation for fine reservoir prediction.
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