Sparse log-domain deconvolution with offset: a Gulf of Mexico example
نویسنده
چکیده
Being interested by a field data application of Marchenko imaging, I identify a Gulf of Mexico 2-D line that I deem appropriate for the job. One of the main requirements of Marchenko imaging is to have deconvolved data. For this dataset and task, I use a non-minimum phase deconvolution approach in the lag-log domain: It can estimate wavelets of any length, shape and amplitude, and yields deconvolved data with clear polarities. This is the first attempt at using this deconvolution technique to process offset panels. In this paper I use one set of parameters for all panels, estimating one wavelet per offset: The time variability is not accounted for yet. Deconvolution results show that the wavelet’s footprint (including source/receiver ghosts and bubble effects) is significantly reduced throughout the entire volume.
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