Improving Repeatability of Land Seismic Data Using Virtual Source Approach Based on Multidimensional Deconvolution

We present a new redatuming workflow developed for improving the repeatability of seismic data and designed specifically to account for changes in the source signatures or variations in downgoing fields in general. The new approach is based on the virtual source method with the same potential for reducing non-repeatability, associated with acquisition geometry changes and variations in the near surface. To correct for changes in the source wavelet between surveys, we suggest deconvolving the virtual source gather of the monitor survey with the point-spread function (PSF) of the same survey, and immediately convolving with the PSF of the base or reference survey. The PSF governs the radiation pattern of the virtual source. Trying to completely deconvolve the effects of individual PSFs on each virtual source response may degrade repeatability due to possible amplification of noise. Instead, we try to equalize radiation patterns of the virtual sources across all repeat surveys by reassigning a new reference PSF to all surveys. We apply the deconvolution-convolution method to a field 4D dataset with buried receivers and demonstrate significant improvement in repeatability.