Prestack Seismic Data Target Processing Methods Oriented AVO Analysis

Pre-stack seismic data pre-processing is the key to AVO analysis and inversion.To improve the accuracy of pre-stack inversion and AVO analysis,we need to make pre-stack seismic data preprocessing.There are many factors,including random noise,residual moveout and preserved amplitude processing,to lead to reduce the quality of the pre-stack seisimic data sets.In this paper,we use the sparse representation method to denoise random noise of pre-stack seismic data sets for improving the signal to noise ratio and resolution.And the amplitude of reflector events of useful signal can be effective preserved,reducing the impact of AVO characteristics due to amplitude changes of events.A basic assumption of AVO theory is that the reflectors being measured are horizontal,but the real seismic data being processed remain residual moveout,resulting in the phenomenon of bending reflected events.By phase substitution method and model residual moveout correction iterative method to make CMP or CRP gathers flattening,We use phase substitution method and model residual moveout correction iterative method to make CMP or CRP gathers flattening and show the tendency of AVO characteristics.Angle gathers demines the reliability of AVO analysis and inversion results.Local level is more complex geological structure,the use of extraction methods based on ray theory angle gathers no longer meet the requirements of AVO analysis and inversion.This paper develops ture amplitude wave equation depth migration method to extract angle domain common image gathers.With offset domain common image gathers(ODCIGs)obtained by our method,the next step is to do a radial-trace transform for ODCIGs in the Fourier domain to gain Angle domain common image gathers(ADCIGs).We compare our method with the conventional conversion method and the straight-ray line PSTM method,and analyze the effectiveness of the proposed method and its AVA properties.Theoretical analysis and numerical experiments show that ADCIGs by our method have comparatively large angle range and true amplitude.So ADCIGs are more suitable for AVA analysis and inversion.