Blind seismic deconvolution of single channel using instantaneous independent component analysis

This paper provides a new statistical approach to solve blind seismic deconvolution problem for a single channel using independent component analysis (ICA). Our technique consists of three steps. Firstly, a transformation method that maps the seismic trace convolution model for a single channel into multiple input multiple output (MIMO) instantaneous ICA model using zero padding matrices. Secondly, whitening the observed seismic trace by incorporating the zero padding matrixes is conducted as a pre-processing step to exploit the sparsity of the mixing matrix. Finally, a novel logistic function that matches the sparsity of reflectivity sequence distribution has been proposed and fitted into the information maximization algorithm to obtain the demixing matrix. Simulated experiments indicate our new algorithm outperforms the conventional independent component analysis (ICA) algorithm. The mean square error (MSE) is used to measure the efficiency of the proposed algorithm.