Abstract: Seismic deconvolution is essential for extracting layer information from noisy seismic data, but it is an ill-posed problem with nonunique solutions. Inspired by classical optimization ...
Picture a familiar scene: You open the fridge before work, realize the milk is out, remember the soccer sign-up fee is due tonight, and get a daycare email about tuition going up next month. Your ...
Abstract: Effective noise suppression and data quality enhancement are critical in seismic data processing. Over the years, many traditional and deep learning (DL) methods have been proposed and ...
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