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Recovery of seismic wavefields based on compressive sensing by an l_1-norm constrained trust region method and the piecewise random subsampling

【摘要】:正Due to the influence of variations in landform,geophysical data acquisition is usually subsampled. Reconstruction of the seismic wavefield from subsampled data is an ill-posed inverse problem.Compressive sensing(CS) can be used to recover the original geophysical data from the subsampled data.In this paper,we consider the wavefield reconstruction problem as a CS and propose a piecewise random subsampling scheme based on the wavelet transform.The proposed sampling scheme overcomes the disadvantages of uncontrolled random sampling. In computation,an l_1-norm constrained trust region method is developed to solve the CS problem.Numerical results demonstrate that the proposed sampling technique and the trust region approach are robust in solving the ill-posed CS problem and can greatly improve the quality of wavefield recovery.

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