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Structural Filter (SF) is a smoothing filter used in pre-stack noise reduction that preserves edge while removing noise. Structural Filter can handle abnormal single high amplitude event, outliers, and strong random noise in pre-stack domain. By preserving edge effect, the filter can also preserve lateral amplitude variation with offset (AVO) in most horizontal and dipping events presented in seismic gathers. Structural Filter as a robust pre-stack noise suppression technique play a very important role in AVO analysis because CDP stacking, the most powerful noise suppression tool in seismic processing is not available in pre-stack seismic data processing.
Focused on Evaluate and analyze Structural Filter in real seismic data, during this study Structural Filter (SF) was applied to Common Midpoint (CMP) and Common Reflection (CRP) Gathers in eight 2D seismic lines from Llanos Basin, Colombia. Both stacked section after filtered CMP and CRP gathers observe enhancement of seismic reflector’s continuity which confirm the edge preserving property on Structural Filter. In CMP gathers SF shows enhancement in Amplitude variation with Offset (AVO) while removing random noise. During the filtering process the data’s Signal to Noise ratio can be significantly diminished if the filter parameter is chosen very strong, However this problem can be overcome by combining SF with pre-stack F-XY decon. Because the presence of dipping layers that disagree with the basic assumption of CMP gathers, Structural Filter was applied to CRP gathers. the result show that the filter preserved true amplitude while suppressed noise and improved Signal to Noise (S/N ) ratio. The application of Structural Filter has produced higher quality Angle Gathers, and therefore contributed to the possibility to get more accurate results when performing AVO analysis.