Paper Summary
Here we review several of the model building techniques introduced over the past decade or so, with emphasis on the assumptions and limitations of each technique. Model building techniques are generally divided into two phases: ‘picking’, and, ‘inverting’. The errors and assumptions in these two phases are quite distinct. Picking may take place on a single offset (or the stack) for
various horizons, or for a series of offsets in the gathers. Picking may also be performed before or after an initial migration. If picking takes place before migration, then the picking error may be large, as for complex environments it is difficult to track or distinguish the various arrival branches of diffraction hyperboloids. Given that manual picking can be tedious; various schemes have been developed for automating this part of the process. In addition, various data reduction schemes can be employed, such as stacking, so that the picking need only be done on one data volume (the zero offset cube, for example) instead of on many finite-offset volumes.