%0 Journal Article
%T Imaging 3D Sea Surfaces from 3D Dual-Sensor Towed Streamer Data
%A Okwudili C. Orji
%A Walter S£¿llner
%A Leiv-J. Gelius
%J International Journal of Geophysics
%D 2013
%I Hindawi Publishing Corporation
%R 10.1155/2013/387175
%X 3D realistic sea surface imaging from 3D dual-sensor towed streamer data is presented. The technique is based on separating data acquired by collocated dual-sensors into up-going and down-going wavefields. Subsequently, these wavefields are extrapolated upwards in order to image the sea surface. This approach has previously been demonstrated using 2D data examples. Here, the focus is on 3D data. Controlled 3D data based on the Kirchhoff-Helmholtz algorithm is generated, and the 3D sea surface imaging technique is applied. For coarsely spaced streamers from 3D field data, the technique is applied streamerwise (i.e., 2D wavefield separation, extrapolation, and imaging). In the latter case, the resulting sea surface profiles corresponding to each time frame are interpolated to demonstrate that the main sea surface characteristics are preserved, and artefacts due to 2D processing of 3D data are mainly limited to areas corresponding to large angles of incidence. Time-varying sea surfaces from two different 3D field data are imaged. The data examples were acquired under different weather conditions. The imaged sea surfaces show realistic wave heights, and their spectra suggest plausible speeds and directions. 1. Introduction In marine seismic acquisition, rough sea surfaces cause amplitude and phase perturbations in the acquired seismic data [1]. However, the corrections applied to the data during processing are often inadequate. In addition to the time-varying nature of the sea surface, seismic streamer depth may also vary with time. This is more visible in time-lapse seismic imaging [1] where successive seismic images of producing field aid geophysicists in identifying bypassed oil, but the effects of time-varying sea surface prove to be a challenge when these images are matched. This is because the temporal distortions introduced in the data by a time-varying rough sea (and fluctuating streamer depth) are neglected. Remote sensing can provide detailed (i.e., smaller wavelengths of the sea surface are imaged) digital elevation models of a sea surface using across-track interferometric synthetic aperture radar (InSAR) [2] (e.g., Schulz-Stellenfleth et al. 2001). However, these elevation models are distorted (depending on the amplitude of the ocean swell) because of the continuous motion of the sea wave. In addition, time-varying sea surface information is not available from satellites because of data size. Moreover, the acquired data may not be ideal for correcting sea surface distortion of marine seismic data. On the other hand, dual-sensor technology can
%U http://www.hindawi.com/journals/ijge/2013/387175/