Resumo:
The construction of seismic images through reverse time migration (RTM) on pre-stacked data and in the time domain requires the cross-correlation between the wavefield of the direct propagation of the source and the one coming from the reverse propagation of the receivers. In the present work, in addition to what is conventionally done, RTM will be executed by direct propagation of the source wavefield and reverse propagation of the field at the receivers performed simultaneously and at each extrapolation step, being transformed to the frequency domain. In this new domain, the imaging condition is applied, and the image is built without storing the direct propagation snapshots of the source.
Furthermore, such RTM results are input for least-squares RTM (LSRTM) in the image domain. There are several ways to do LSRTM and obtain an approximation of the inverse of the Hessian matrix to remove its effect on the final migrated image. This matrix is the defocusing operator responsible for the blurring effect in the migrated image from the conventional migration. In this paper, we seek to calculate non-stationary focusing filters on the image domain that approximate the Hessian and then remove it from the migrated image. Finally, it is shown here to be more appropriate, in the least-squares approach, to estimate the filter that approximates the Hessian and then assess the final image instead of the filter that matches the inverse of the Hessian from the application of this, obtaining the final image. The results obtained here were generated using the Marmousi and Pluto models, demonstrating that the approach of using matching filters in the image domain can produce results superior to those obtained with conventional RTM.
