The extremely large size of typical seismic imaging problems has been one of the major stumbling blocks for iterative techniques to attain accurate migration amplitudes. These iterative methods are important because they complement theoretical approaches that are hampered by difficulties to control problems such as finite-acquisition aperture, sourcereceiver frequency response, and directivity. To solve these problems, we apply preconditioning, which significantly improves convergence of least-squares migration. We discuss different levels of preconditioning that range from corrections for the order of the migration operator to corrections for spherical spreading, and position and reflector-dip dependent amplitude errors. While the first two corrections correspond to simple scalings in the Fourier and physical domain, the third correction requires phase-space (space spanned by location and dip) scaling, which we carry out with curvelets. We show that our combined preconditioner leads to a significant improvement of the convergence of least-squares 'wave-equation' migration on a line from the SEG AA' salt model.
SUMMARYIn this paper, we introduce a preconditioner for seismic imaging-i.e., the inversion of the linearized Born scattering operator. This preconditioner approximately corrects for the "square root" of the normal-i.e., the demigration-migration operator. This approach consists of three parts, namely (i) a left preconditoner, defined by a fractional time integration designed to make the migration operator zero order, and two right preconditioners that apply (ii) a scaling in the physical domain accounting for a spherical spreading, and (iii) a curvelet-domain scaling that corrects for spatial and reflectordip dependent amplitude errors. We show that a combination of these preconditioners lead to a significant improvement of the convergence for iterative least-squares solutions to the seismic imaging problem based on reverse-time migration operators.
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