Seismic data compression and QC using GenLOT

Modern seismic surveys with higher-precision numerization (24-bits A/D converters) have led to ever increasing amounts of seismic data. Management of these large datasets becomes critical, not only for transmission, but also for storage, processing and interpretation. Compression algorithms have been proposed in the geophysicists' community over the past few years as a way to e ectively manage seismic data. For instance, wavelet based compression algorithms can represent seismic data using only a fraction of the original data size. Recently, several works on generalized lapped transform (GenLOT) demonstrate its advantage over wavelets for conventional image compression. Their features are well suited to seismic data properties and have led to better results than for wavelets, in terms of signal-to-noise ratio. In this study we compare GenLOT with wavelet compression results. We have implemented algorithms in a new embedded scheme allowing exact bit rate compression, and providing straight-forward quality control (QC) checks. Simulations are performed on several types of datasets, including shot, CDP gathers and stack sections. The paper is organized as follows: Section 2 brie y reviews seismic data compression, discusses transform-based coding and the idea of embedded zerotree coding. Here one can easily incorporate quality control issue as part of embedded zerotree coding algorithm. Section 3 reviews the GenLOT theory and motivates why GenLOT transform should give better performance as compared to wavelet transform. Section 4 discusses the simulation results, comparing the performance of the GenLOT-based and waveletbased algorithms. Section 5 concludes the paper and discusses future work.