A joint velocity model building method with Gaussian beam tomography and full waveform inversion for land seismic data

The full waveform inversion (FWI) based on prestack seismic wavefield fitting is facing a few challenges in the application, for instances, low signal-to-noise ratio (SNR) land seismic data, missing low frequency information, complicated near-surface, and huge memory needed for massive 3D seismic data processing.In terms of low-precision land seismic migrations, we propose in this paper a velocity model building method by Gaussian Beam tomography, which not only makes up medium wave-number components unachievable in conventional methods based on ray tracing tomography but also provides FWI with a high precise macroscopic velocity model that helps to avoid effectively cycle skips.Besides, in order to reduce the dependency of inversion on low frequencies, we replace the L2 norm with a cross-correlation function based on phase matching, which figures out validly the problem of intensive computing of FWI.Furthermore, with a self-adjoint forward operator from pseudo-conservative wave equations, the gradient computing capacity based on an adjoint-state method is enhanced dramatically, which improves the inversion adaptation and realizes a high-resolution velocity model building for land seismic data. © 2019, Editorial Department OIL GEOPHYSICAL PROSPECTING. All right reserved.