Sparse Multichannel Blind Deconvolution of Seismic Data via Spectral Projected-Gradient

Wavelet Estimation via Sparse Multichannel Blind Deconvolution

Multichannel Semi-blind Sparse Deconvolution of Seismic Signals

Seismic deconvolution is associated with recovering the reflectivity series from a seismic signal when the wavelet is known. In this paper, we address the problem of multichannel semiblind seismic deconvolution, where the wavelet is unknown and there is some uncertainty in the assumed wavelet. We present a novel, two-stage iterative algorithm that recovers both the reflectivity and the wavelet....

Modified Sparse Multichannel Blind Deconvolution

Multichannel Blind Deconvolution of Seismic Signals

A new algorithm for simultaneous wavelet estimation and deconvolution of seismic reflection signals is given. To remove the inherent ambiguity in this blind deconvolution problem, we introduce relevant a priori information. Our major assumption is sparseness of the reflectivity, which corresponds to a layered earth model. This allows non-minimum phase wavelets to be recovered reliably and close...

Multichannel blind seismic deconvolution using dynamic programming

In this paper, we present an algorithm for multichannel blind deconvolution of seismic signals, which exploits lateral continuity of earth layers by dynamic programming approach. We assume that reflectors in consecutive channels, related to distinct layers, form continuous paths across channels. We introduce a quality measure for evaluating the quality of a continuous path, and iteratively appl...