| 摘要 |
Methods and systems for variable wavelet correction are described. A variable depth dataset is deghosted before presentation to a multiples prediction step of multiples elimination model. In another aspect, the multiples prediction is reghosted before presentation to and adaptive subtraction step of the multiples elimination model. A source-side zero-phasing signature can be applied before deghosting and a predefined gain can be applied in the low and high frequency sides as part of deghosting and reghosting to compensate for the squaring effect produced by convolving wavelets.
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