Comparative analysis of matching pursuit algorithms for Kirchhoff migration on compressed data

Currently, the amount of recorded data in a seismic survey is order hundreds Terabytes. The processing such implies significant computational challenges. One them I/O bottleneck between main memory and node memory. This results from fact that disk access speed thousands-fold slower than co-processors (eg. GPUs). We propose special Kirchhoff migration develops process over compressed data. by using three well-known Matching Pursuit algorithms. Our approach seeks to reduce number accesses required operator add more mathematical operations traditional migration. Thus, we change slow (memory access) for fast (math operations). Experimental show proposed method preserves, large extent, attributes image compression ratio up 20:1.