Seismic Data Compression Based On Sparse Decomposition

Along with the development of seismic prospecting, and the application of advanced technology, the amounts of seismic data increase rapidly, and large numbers of redundant data are included in it. Actually the practical seismic exploration often need to transmit a large number of seismic data which is collected in remote areas or at sea to the Mainland for analysis and processing via satellite. Therefore, the study of long-distance transmission of seismic data is very important. The costs of using satellite transmiting data is very high, we all want to be able to reduce costs through effective treatment, for this purpose, also in order to achieve the certain compression ratio and satisfiy the reconstruction precision of seismic data, this paper studys the seismic data compression based on sparse decomposition and a new seismic data coding scheme is proposed for seismic data of one or two-dimensional based on the result of seismic data sparse decomposition.In this thesis, the signal sparse decomposition is introduced firstly, and as the formation of signal sparse decomposition result, sparse signal presentation is introduced. In the following, matching pursuit is introduced. Matching pursuit is the most popular algorithm of signal sparse decomposition and much esaier to understand and to apply than the other algorithms. Next, constructing the over-complete dictionary for one-dimensional seismic data compression is studied and sparse decomposition of one-dimensional seismic data is done, also the distribution of seismic data sparse decompositin result is analyzed and a seismic data coding scheme is then proposed based on the seismic data sparse decompositin results. Finally, one-dimensional seismic data compression is achieved and improvements is made. After studying one-dimensional seismic data compression, this paper discussing the compression of two-dimensional seismic data. Applying the difference method to two-dimensional seismic data compression, then constructing the over-complete dictionary which is suitable to compression for it, later doing sparse decomposition, and proposing a reasonable coding scheme. This makes the effect of compression much better.The experimental results show that the seismic data compression scheme based on sparse decomposition proposed in this paper is quit effective, and whatever the compression ratio and reconstruction quality are controllable.