Sparsity‐enhanced wavelet deconvolution

We propose a three‐step bandwidth enhancing wavelet deconvolution process, combining linear inverse filtering and non‐linear reflectivity construction based on a sparseness assumption. The first step is conventional Wiener deconvolution. The second step consists of further spectral whitening outside the spectral bandwidth of the residual wavelet after Wiener deconvolution, i.e., the wavelet resulting from application of the Wiener deconvolution filter to the original wavelet, which usually is not a perfect spike due to band limitations of the original wavelet. We specifically propose a zero‐phase filtered sparse‐spike deconvolution as the second step to recover the reflectivity dominantly outside of the bandwidth of the residual wavelet after Wiener deconvolution. The filter applied to the sparse‐spike deconvolution result is proportional to the deviation of the amplitude spectrum of the residual wavelet from unity, i.e., it is of higher amplitude; the closer the amplitude spectrum of the residual wavelet is to zero, but of very low amplitude, the closer it is to unity. The third step consists of summation of the data from the two first steps, basically adding gradually the contribution from the sparse‐spike deconvolution result at those frequencies at which the residual wavelet after Wiener deconvolution has small amplitudes. We propose to call this technique “sparsity‐enhanced wavelet deconvolution”. We demonstrate the technique on real data with the deconvolution of the (normal‐incidence) source side sea‐surface ghost of marine towed streamer data. We also present the extension of the proposed technique to time‐varying wavelet deconvolution.     

Provenance and weathering history of the maastrichtian shale member of the Patti Formation,southern Bida Basin,Nigeria

The present study is focused on the geochemical characterization and provenance of the shale member of the Maastrichtian Patti Formation which is well represented at the centre of the southern Bida Basin in Nigeria. The major element composition of the studied shales and clays compare favourably with the reference shales, however, the trace elements vary slightly. Application of binary plot of TiO₂ versus Al₂O₃ and Al₂O₃/TiO₂ ratios of the studied shale samples show mixed mafic to felsic igneous sources. The chemical composition (plot of SiO₂ versus Log (K₂O/Na₂O) indicates active to passive continental margin province, however, a minor derivation from recycled provenance is probable. Intense chemical weathering based on the high values of Chemical Index Alteration (CIA), Chemical Index of Weathering (CIW) and Zr values obtained from the shale and clay samples a warm humid condition is suggested. The high values also probably suggest predominance of clay minerals and low feldspar. This is supported by the XRD (X-Ray Diffractometer) data which indicates predominance of kaolinite in the samples.