Joint denoising method of seismic data via BP neural network and SVD algorithm
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TN911.7;P631

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    Abstract:

    In the traditional denoising method of the seismic data, it has poor effect because it depends on prior data too much. In order to suppress seismic data noise more effectively, a joint denoising method based on the respective characteristics of BP network and SVD algorithm is proposed. The proposed method has carried on the thorough discussion to the BP network structure and the experimental methods. The determined experimental method is as follows: firstly, the noisy seismic data are separated by BP network, and then the output noise is reconstructed by SVD algorithm, which is the output noise of the joint algorithm. Finally, the denoised seismic data can be obtained by subtracting the noisy seismic data from the output noise. Experiments on prestack and poststack seismic data demonstrate that the proposed method is feasible and effective. Compared with the traditional denoising algorithm, the MSE (mean square error) of the proposed method is lower and the SNR (signaltonoise ratio) is higher, which shows that it has better denoising effect on actual seismic data.

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History
  • Received:
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  • Online: June 15,2023
  • Published: January 31,2020
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