We present the first results of a new method of estimating anisotropic migration velocities: the computation of anisotropic velocity spectra from Residual Moveout (RMO) transformation in anisotropic Angle-Domain Common-Image Gathers (ADCIGs). In the first part of this paper, we formulate the estimation of the anisotropic parameters from the RMO curves as an inverse problem. This analysis reveals how accurately we can estimate the parameters, what trade-offs exist between them, and eventually which iterative estimation procedure we should use. In the second part, we compute the anisotropic velocity spectra of synthetic data and estimate anisotropic migration velocities.
As it was observed that the approximation of an isotropic subsurface was not geologically grounded and that isotropic migration methods could give results inconsistent with other data (e.g. from wells), anisotropic migration became an important focus of research and is now widely used in the industry. However, estimating anisotropic migration velocities remained the key to quality of imaging and accurate reflector positioning.
Today, migration velocity analysis (MVA) is the procedure most commonly employed to estimate isotropic migration velocity in complex media. However, it is still less mature for anisotropic applications and recent progress has been made toward the development of anisotropic MVA only in conjunction with Kirchhoff migration. The work on residual moveout (RMO) in anisotropic angle-domain common-image gathers (ADCIGs) presented in (3) and (4), by giving a mathematical relationship that links RMO in anisotropic ADCIGs to anisotropic migration velocity errors, opened the way to new anisotropic MVA methods that can be performed in conjunction with wavefield-continuation migration.
In this paper, we present the preliminary results from the computation of anisotropic velocity spectra from the RMO transformation in anisotropic ADCIGs. In the first part, we formulate the anisotropic velocity estimation as an inverse problem. We first analyze the attainable accuracy of the estimated parameters, and the trade-off between them. This allows us to specify an appropriate iterative estimation procedure. In the second part, we compute anisotropic velocity spectra of synthetic data, estimate anisotropic migration velocities and comment on the results in light of the conclusions from the first part.