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- W3022697105 abstract "P 159 COHERENT NOISE ATTENUATION USING INVERSE PROBLEMS AND PREDICTION ERROR FILTERS 1 SUMMARY ANTOINE GUITTON Department of Geophysics Stanford University Stanford CA 94305 USA Two iterative methods that remove coherent noise during the inversion of 2-D prestack data are tested. One method approximates the inverse covariance matrices with prediction error filters (PEFs) and the other introduces a coherent noise modeling operator in the objective function. This noise modelling operator is a PEF that has to be estimated either before the inversion from a noise model or directly from the data. These two methods lead to independent identically distributed (IID)" @default.
- W3022697105 created "2020-05-13" @default.
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- W3022697105 date "2001-01-01" @default.
- W3022697105 modified "2023-09-26" @default.
- W3022697105 title "Coherent Noise Attenuation Using Inverse Theory and Prediction Error Filters" @default.
- W3022697105 doi "https://doi.org/10.3997/2214-4609-pdb.15.p159" @default.
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