--> Superior Definition of Geologic Features by Running Geometric Attributes on Preconditioned Seismic Data
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Superior Definition of Geologic Features by Running Geometric Attributes on Preconditioned Previous HitSeismicNext Hit Previous HitDataNext Hit

Abstract

3D Previous HitseismicNext Hit 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 feathering, result in irregularity in sampling of the Previous HitmarineNext Hit Previous HitdataNext Hit. Since the days of the single streamers, the inlines are usually well sampled and the sampling in the crosslines is usually coarse. Land Previous HitacquisitionNext Hit encounters a different suite of obstacles, such as habitation, lakes and buildings. These, coupled with limited recording capacity and greater cost results in missing Previous HitdataNext Hit or ‘holes’ in Previous HitseismicNext Hit Previous HitdataNext Hit coverage. Sparse or missing Previous HitdataNext Hit 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 ‘Previous HitacquisitionNext Hit footprint’. Previous HitSeismicNext Hit Previous HitdataNext Hit with geometry regularization issues give rise to artifacts on geometric attribute displays. Obviously, the ideal way to fill in the missing Previous HitdataNext Hit gaps would be to reshoot the Previous HitdataNext Hit in those areas. However, infill Previous HitacquisitionNext Hit would be extremely expensive per Previous HitdataNext Hit point. Such regularization problems have been addressed at the processing stage by prediction or population of missing traces in Previous HitseismicNext Hit Previous HitdataNext Hit, referred to as interpolation. One of the more sophisticated methods for Previous HitdataNext Hit interpolation, which is multi-dimensional, operating simultaneously in different spatial dimensions (as many as five) and is able to predict the missing Previous HitdataNext Hit with more accurate amplitude and phase variations is 5D interpolation. As it regularizes the geometry of the Previous HitseismicNext Hit Previous HitdataNext Hit, it addresses the root cause of the footprint arising due to the Previous HitacquisitionNext Hit irregularities as well. We demonstrate the application of 5D interpolation on Previous HitseismicNext Hit Previous HitdataNext Hit and show how it aids some of the Previous HitseismicNext Hit attributes derived from them. Coherence and curvature attributes computed on regularized Previous HitseismicNext Hit Previous HitdataTop yield displays clear of these artifacts, lead to more confident displays as well as accurate interpretations.