In processing of ocean-bottom-node (OBN) data, vertical particle velocity (Vz) data, recorded by geophones, and pressure (P) data, recorded by hydrophones, can be used conjunctively for up- and down-going wavefield separation. However, shear noise attenuation needs to occur in the Vz data before it can be matched to the P data. The noise attenuation and the matching can be achieved in one step by local attribute matching in the dual-tree complex wavelet transform (DTCWT) domain. Shear noise on Vz data can be characterized as low frequency and composed of a wide range of local dips. Conventional DTCWT does recursive band analysis only in the LL-band (low-f and low-k band). Therefore, shear noise with k in the higher half-band cannot be well-resolved in the frequency domain due to the poor frequency resolution in the LH band. As a result, the attenuation of high-k shear noise can be inadequate in conventional DTCWT domain. This paper proposes a new scheme to do 2D complex wavelet transformations that can provide adaptive angular-resolving capability for each analysis stage and thus solve the problem of poor high-k shear noise suppression with conventional 2D DTCWT.
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