ABSTRACT Seismic data are inadequately or irregularly sampled, particularly when there are big gaps, which will produce artifacts in the seismic imaging. The reconstruction can be posed as an inverse problem, which is known to be ill-posed and requires constraints to achieve unique and stable solutions. In this abstract, we propose an iterative scheme to reconstruct big gaps using least-squares method with slope constraint. In the proposed method, the slope estimation is a very important step. We apply an iterative scheme to estimate the slope field. In the first iteration, the smooth radius must be large to estimate smooth dip from the decimated data to guarantee the stability of inversion. In the later iterations, the smooth radius will be shortened in order to get more accurate dip estimation and good reconstruction result. We compare the proposed method and the well-known projection onto convex sets (POCS) method on the synthetic and field data examples. The interpolation results illustrate the advantage of the proposed method in constructing big gaps.
Presentation Date: Tuesday, October 18, 2016
Start Time: 3:45:00 PM
Location: 148
Presentation Type: ORAL