Blind deconvolution of seismic signals with non-white reflectivities
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Abstract
Seismic deconvolution technology is important in seismic data processing. We propose a new blind deconvolution algorithm for simultaneous wavelet estimation and deconvolution of seismic data. Optimal seismic deconvolution can be achieved by the combined application of a non-white reflectivity model and the blind deconvolution method. We incorporate a scaled Gaussian noise (SGN) model of seismic reflection coefficients into the seismic blind deconvolution method. The SGN model has the property of scale invariance. We present a framework to generalise the conventional deconvolution procedure to handle reflection coefficients that do not follow the white-noise model. Reflection coefficients are assumed to have an autocorrelation function with a power spectrum roughly proportional to some power of frequency.
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