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Prestack seismic inversion method based on support vector machine
YANG Pei-jie, YIN Xing-yao
(Faculty of Geo-Resource and Information in China University of Petroleum,Dongying 257061,Shandong Province, China)
Abstract:
By analyzing the conventional seismic inversion methods and overcoming their defects,a prestack seismic inversion method based on support vector machine was proposed ensuring the inversion effect. The method can extract much more reservoir physical properties than conventional poststack acoustic impedance inversion,so it is suitable for reservoir physical property and oil and gas property inversion. And it can directly estimate independent elastic parameters using seismic data. This method eliminates the need for any approximations of the Zoeppritz's equations or assumptions about the independent elastic parameters, initial model and constraint of well logging. The inversion results show that the proposed method is characterized by high inversion velocity, good stability and great antinoise ability. It is suitable for further popularization and application.
Key words:  prestack seismic inversion  support vector machine  Zoeppritz's equations  statistical learning theory