Simultaneous seismic data denoising and reconstruction via multichannel singular spectrum analysis
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Abstract
Abstract We present a rank reduction algorithm that permits simultaneous reconstruction and random noise attenuation of seismic records. We based our technique on multichannel singular spectrum analysis (MSSA). The technique entails organizing spatial data at a given temporal frequency into a block Hankel matrix that in ideal conditions is a matrix of rank k, where k is the number of plane waves in the window of analysis. Additive noise and missing samples will increase the rank of the block Hankel matrix of the data. Consequently, rank reduction is proposed as a means to attenuate noise and recover missing traces. We present an iterative algorithm that resembles seismic data reconstruction with the method of…
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Topics
Keywords
- Singular value decomposition
- Algorithm
- Noise reduction
- Low-rank approximation
- Singular value
- Synthetic data
- Noise (video)
- Hankel matrix
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