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Superior Definition of Geologic Features by Running Geometric Attributes on Preconditioned Seismic Data


3D seismic surveys are usually designed in a way that the subsurface features are regularly sampled in different dimensions, comprising the spatial coordinates, offsets and azimuths. Many processing algorithms require this regularity for their optimum performance. In reality, obstacles such as platforms at sea, as well as tides and currents that give rise to Previous HitfeatheringTop, result in irregularity in sampling of the marine data. Since the days of the single streamers, the inlines are usually well sampled and the sampling in the crosslines is usually coarse. Land acquisition encounters a different suite of obstacles, such as habitation, lakes and buildings. These, coupled with limited recording capacity and greater cost results in missing data or ‘holes’ in seismic data coverage. Sparse or missing data create problems while processing, as the different algorithms applied pre-stack or post-stack demand regularity in the offset and azimuth dimensions for optimum performance. Non-uniformity in offsets and azimuths leads to inconsistencies in fold that follow a regular pattern we refer to as ‘acquisition footprint’. Seismic data with geometry regularization issues give rise to artifacts on geometric attribute displays. Obviously, the ideal way to fill in the missing data gaps would be to reshoot the data in those areas. However, infill acquisition would be extremely expensive per data point. Such regularization problems have been addressed at the processing stage by prediction or population of missing traces in seismic data, referred to as interpolation. One of the more sophisticated methods for data interpolation, which is multi-dimensional, operating simultaneously in different spatial dimensions (as many as five) and is able to predict the missing data with more accurate amplitude and phase variations is 5D interpolation. As it regularizes the geometry of the seismic data, it addresses the root cause of the footprint arising due to the acquisition irregularities as well. We demonstrate the application of 5D interpolation on seismic data and show how it aids some of the seismic attributes derived from them. Coherence and curvature attributes computed on regularized seismic data yield displays clear of these artifacts, lead to more confident displays as well as accurate interpretations.