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A Global-scale AVO-based Pre-stack QC Workflow - An Ultra-dense Dataset in Tunisia
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 78th EAGE Conference and Exhibition 2016, May 2016, Volume 2016, p.1 - 5
Abstract
Throughout a processing sequence, data AVO must be preserved in order to perform AVO analysis on the final dataset which will be used for reservoir characterization. We therefore need an efficient AVO-based pre-stack QC which assesses the impact of a processing step on the AVO.
In this paper we introduce a pre-stack data QC method based on AVO which can be applied to all types of 3D datasets. It consists firstly of data reduction of the pre-stack data through angle stacks. Then a robust AVO model is extracted using dip-consistent macro-binned AVO fitting. Finally, a comparison of the robust AVO model to the seismic data is performed using quantitative attributes such as the correlation and NRMS (normalized root-mean-square) of the data and the model. The main strength of this method lies in its efficient applicability to large amounts of data, without well control. This is demonstrated via application of the method to an ultra-dense land dataset from Tunisia.