The theoretical best-possible resolution can be predicted using Beylkin’s formula. This formula gives answers to the effect on resolution of frequency, aperture, offset, and acquisition geo-metry. In this paper, for each 3-D single-fold data set a spatial wavelet is obtained from migration of an event that attributed to diffraction. Then the width of the spatial wavelet is compared to the resolution predicted by Beylkin’s formula. The measured widths confirmed the theoretical predict-tions (i.e. zero-offset data produces the best possible resolution; 3-D shot records produces the worst resolution, and common-offset gathers and cross-spreads producing the intermediate resolution. It is shown that the effects of sampling and fold cannot be derived directly from Beylkin’s formula; these effects are analyzed by looking at the migration noise rather than width of the spatial wavelet. Our results indicated that random coarse sampling may produce somewhat less migration noise than regular coarse sampling, though it cannot be as good as regular dense sampling. Generally speaking, in-creasing fold does not improve the theoretically best possible resolution. However, as noise always has a detrimental effect on the resolvability of events, fold by reducing noise will improve resolution in practice. Required algorithms were written by authors in MATLAB environment