Dreamlet transform applied to seismic data compression and its effects on migration

Local cosine/sine basis is a localized version of cosine/sine basis with a smooth window function. It has orthogonality and good time and frequency localization properties together with a fast algorithm. In this paper, we present a new method combining the main idea of local cosine/sine bases, multi-scale decomposition and the dispersion relation to form a multi-scale, multi-dimensional self-similar dreamlet transform. Meanwhile, a storage scheme based on the dreamlet decomposition is proposed by using zig-zag sequence. We apply this method to the SEG-EAGE salt model synthetic poststack data set for data compression. From the result, almost all the important features of the data set can be well kept, even in high compression ratio. Using the reconstructed data for migration, we can still obtain a high quality image of the structure. Through comparing with other decomposition and compression schemes, we believe that our sheme is more closely related to the physics of wavefield and has a better performance for seismic data compression and migration.