Fracture property identification method based on shrinkage factor particle swarm optimization

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In the multi-wave and multi-component seismic exploration,shear-wave will be split into fast wave and slow wave,when it propagates in anisotropic media. Then the authors can predict polarization direction and density of crack and detect the development status of cracks underground according to shear-wave splitting phenomenon. The technology plays an important role and shows great potential in crack reservoir detection. In this study,the improved particle swarm optimization algorithm based on shrinkage factor is combined with the Pearson correlation coefficient method to obtain the fracture azimuth angle and density. The experimental results show that the modified method can improve the convergence rate,accuracy,anti-noise performance and computational efficiency. In the multi-wave and multi-component seismic exploration, shear-wave will be split into fast wave and slow wave, when it propagates in anisotropic media. Then the authors can predict polarization direction and density of crack and detect the development status of cracks The technology plays an important role and shows great potential in crack reservoir detection. In this study, the improved particle swarm optimization algorithm based on shrinkage factor is combined with the Pearson correlation coefficient method to obtain the fracture The experimental results show that the modified method can improve the convergence rate, accuracy, anti-noise performance and computational efficiency.
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