按照以往的测量矩阵进行实际勘察无法较好地实现地震数据的重构,大多数矩阵设计复杂且元素多样,不符合实际标准.笔者将LDPC矩阵应用到地震勘探采样中,用较少的地震数据来重构完整的地震记录.采用K-SVD字典对数据进行稀疏变换, FISTA算法进行重构.对比以往的随机采样、离散均匀采样和jitter采样, LDPC矩阵更适合三维环境且恢复重构效果更好.对比重构数据的信噪比,三维模拟数据和实际数据都证实了LDPC矩阵信噪比值最高,重构出的数据效果最好.%The existing sampling matrices cannot realize good seismic data reconstruction results, and most of matrices are complicated and have different elements, which are not suitable for seismic prospecting.The authors applied LDPC matrix to seismic data acquisition, using less data to realize complete data reconstruction.The K-SVD dictionary was used for sparse transform, and FISTA reconstruction algorithm was used to recover original da-ta.Compared with previous random sampling, discrete regular sampling and jitter sampling, the LDPC (Low Den-sity Parity Check) matrix was more suitable in 3-D environment and achieved better performance.Comparing SNRs of reconstructed data of different methods, both 3-D simulated data and field data proved that LDPC matrix has the best SNR and performance.
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