Interpolation of Sparse, Wide-Azimuth Onshore and Ocean-Bottom Seismic Data Using a Global, 5- Dimensional Interpolator

Daniel Trad¹*, R. Gareth Williams²**, and Richard Wombell^2
1CGGVeritas, Canada
²CGGVeritas, UK
*[email protected]
**[email protected]

Many 3-D land surveys do not fulfill the requirements of seismic processing techniques, such as migration, which have strict requirements on data sampling in the input seismic data. Although not a substitute for well-sampled field data, interpolation can provide useful data pre-conditioning that allows migration and other processes to work better. Seismic data interpolation has been around for a long time, but only recently have we been able to use complex multi-dimensional algorithms that have the capability to infill large gaps in wide-azimuth 3-D land or ocean-bottom surveys. Earlier algorithms attempted to interpolate data using just three dimensions, whereas in fact data is recorded in five dimensions (shot-x, shot-y, receiver-x, receiver-y and time). If we use all 5 dimensions in an iterative, minimum-norm weighted inversion, we can use all the available information for interpolation and hence obtain optimum results. Furthermore, there is less overlap of aliased and non-aliased data in 5-D than 3-D, and this relaxes the traditional constraints on interpolation. The algorithm has been applied to a number of problems such as: (1) reducing bin size to remove aliasing prior to migration; (2) increasing fold and azimuth distribution within common mid-point bins to allow improved estimation of fracture patterns; and (3) regularization of bins to reduce migration induced noise. These techniques have been used in a variety of structural environments.

AAPG Search and Discovery Article #90077©2008 GEO 2008 Middle East Conference and Exhibition, Manama, Bahrain