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Diffraction wave separation and imaging with deep learning network: application of GPR data

The conventional reflection wave exploration always receives attention from geophysicists and geologist. However, for the identification of small-scale anomalous body and pinchouts, the diffraction wave imaging possess superiority. Basic response of discontinuities and heterogeneities in received data profile takes the form of diffraction wave (Claerbout, 1992; Landa and Keydar, 1998). It carries a significate information of tiny erosional structure or fracture, which can be applied to detect the position of backscatters. Due to its weak energy compared with the specular reflections, diffraction wave cannot be separated completely and imaged clearly. (Klem-Musatov, 1994; Moser and Howard, 2008). In addition, there is less dedicated processing technique in traditional geophysics prospecting to enhance the diffraction wavefield. The separation and migration of diffractions should be more accurate and remain a challenging for the further proposed approaches.