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Seismic data random interference suppression technology research

Author: ChenMeiNian
Tutor: HeBingShou
School: Ocean University of China
Course: Earth Exploration and Information Technology
Keywords: Random interference Signal-to-noise ratio Denoising Singular Value Decomposition Wavelet Transform
CLC: P631.44
Type: Master's thesis
Year: 2010
Downloads: 136
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Abstract


Enhance the effective signal to suppress random noise, low signal-to-noise ratio, the primary task of seismic data processing, but also the difficulty of research in seismic data denoising. Causes, characteristics and classification based on random interference by the analysis of seismic records, used random interference suppression technique is briefly described, and analyze their strengths and weaknesses. Low SNR data for the complex structure, improved singular value decomposition denoising algorithm, wavelet divide Threshold Denoising theoretical data and actual seismic data. The singular value decomposition method is based on coherent denoising technology. When the When input channel concentrated lateral coherence of the valid signal is strong, it can be maintained under the premise of a smaller signal distortion to obtain a better random interference suppression effect, when the effective signal-phase axis is inclined, curved or isolated state, singular value decomposition method to suppress the noise, but also filter out some of the valid signal, resulting in a waste of earthquake information. These shortcomings, singular value decomposition denoising technology to improve the traditional denoising algorithm based on singular value decomposition, by flatten the window seismic data, the singular value decomposition of the data reconstruction and anti-pull equal treatment to overcome conventional singular value decomposition algorithm to filter out random interference, non-the horizontal continuous signal denoising effect limitations in the protection of the effective signal to improve the signal-to-noise ratio of seismic data. The theoretical and experimental data processing results show that, compared with the the global singular value decomposition, partial singular value decomposition method can better deal with tilt, bend, isolated and discontinuous phase axis to obtain better denoising effect. Wavelet analysis is a in the time domain and frequency domain at the same time of the signal a local analysis tool. In this paper, on the basis of the study of wavelet denoising theory wavelet threshold denoising technology to suppress the seismic record random interference. According to the distribution of the noise signal components in different resolutions, the wavelet coefficients using different threshold processing method for processing data reconstruction, and treatment wavelet coefficients, the theoretical data and the measured data simulation denoising effect significant. Combined with local wavelet threshold denoising based on singular value decomposition denoising technology, further suppression of random interference and improve the resolution of seismic data can be better than using only one kind Denoising random interference suppression effect.

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CLC: > Astronomy,Earth Sciences > Geology > Geology, mineral prospecting and exploration > Geophysical exploration > Seismic exploration >
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