A seismic interpolation and denoising method with curvelet transform matching filter |
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| Authors: | Hongyuan Yang Yun Long Jun Lin Fengjiao Zhang Zubin Chen |
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| Institution: | 1.College of Instrumentation and Electrical Engineering,Jilin University,Changchun,China;2.Key Laboratory of Geo-exploration Instruments,Ministry of Education of China (Jilin University),Changchun,China;3.College of Geo-Exploration Science and Technology,Jilin University,Changchun,China |
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| Abstract: | A new seismic interpolation and denoising method with a curvelet transform matching filter, employing the fast iterative shrinkage thresholding algorithm (FISTA), is proposed. The approach treats the matching filter, seismic interpolation, and denoising all as the same inverse problem using an inversion iteration algorithm. The curvelet transform has a high sparseness and is useful for separating signal from noise, meaning that it can accurately solve the matching problem using FISTA. When applying the new method to a synthetic noisy data sets and a data sets with missing traces, the optimum matching result is obtained, noise is greatly suppressed, missing seismic data are filled by interpolation, and the waveform is highly consistent. We then verified the method by applying it to real data, yielding satisfactory results. The results show that the method can reconstruct missing traces in the case of low SNR (signal-to-noise ratio). The above three problems can be simultaneously solved via FISTA algorithm, and it will not only increase the processing efficiency but also improve SNR of the seismic data. |
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