This paper demonstrates a methodology to produce high-resolution AVO reflectivity attribute estimates similar to sparse spike deconvolution. Similar to poststack sparse deconvolution this reflectivity may be converted to impedance provided there are suitable additional constraints. The AVO estimate is performed prior to NMO avoiding the distortions and loss of frequency associated with this process. Long tailed a priori distributions are used to constrain the problem. The resulting sparse reflectivity is able to resolve thin layers and is more reliable than the estimates provided by the traditional AVO analysis that is performed on a sample-by-sample basis on NMO corrected gathers. This greater reliability is due to the classic trade-off between resolution and stability. With the new method a few sparse reflectivity values are estimated with greater certainty than the dense reflectivity at every time sample as in the traditional AVO analysis.
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