Effects of time-varying sea surface in marine seismic data

Abstract

A method of imaging sea surfaces based on marine seismic measurements has recently been developed. The imaging technique is based on extrapolating decomposed wavefields obtained from dual-sensor streamers to the sea surface where an adequate imaging condition is applied. Earlier feasibility tests of the method involved only controlled data associated with frozen sea surfaces. Here, the issue of time-varying effects will be in focus. We introduced a modeling approach based on the Kirchhoff-Helmholtz integral and computed the scattered wavefield from time-varying rough sea surfaces (e.g., Pierson-Moskowitz sea surfaces). We generated data for a realistic wind speed and verify the robustness of the proposed sea surface imaging technique by taking into account possible effects of moving receivers as well as streamers with variable shape. We investigate the feasibility of estimating the surface wave velocity from the spectra of the imaged sea surfaces and finally present a successful application of the sea surface imaging technique to data from the North Sea.

Imaging 3D Sea Surfaces from 3D Dual-Sensor Towed Streamer Data

“…In order to recover the sea surface information from the recorded scattered data, the backward approach could be used. However, our interest is to further validate the sea surface imaging technology proposed by [3][4][5] which is applicable to field data. It is reintroduced here in 3D in order to bring the present work into context.…”

“…However, this method is dependent on the precision of the pressure sensors at very low frequencies (between 0.05 Hz and 0.3 Hz), which is well below normal seismic bandwidth. A method of imaging 2D sea surfaces from 2D seismic data acquired by collocated dual-sensor systems (comprising pressure and particle velocity sensors) has been described by Orji et al [4][5][6]. This paper investigates the robustness of the proposed imaging 2 International Journal of Geophysics technique to reconstruct 3D time-varying sea surfaces from 3D towed dual-sensor streamer data.…”

“…Given the frequency band of typical marine seismic sources and the degree of sea surface roughness, the Kirchhoff method seems to be a valid approach when computing scattered seismic data for marine seismic cases. Orji et al, [5,6] presented a forward modeling approach based on the 2D time-domain Kirchhoff-Helmholtz integral, which can handle 2D time-varying rough sea surfaces, and used it to validate the sea surface imaging technique. Here, 3D extension of the forward modeling tool is used in generating controlled data.…”

“…The depth positions of the maximum image values define the sea surface. Finally, by using a sliding window through the data and repeating the imaging technique for each window, time variable changes of the sea surface can be accounted for [4][5][6].…”

“…Wavefield separation in 3D (e.g., [15][16][17][18][19][20]) is then applied to the modeled dual-sensor data to recover the up-going and down-going pressure fields. Subsequently, the separated wavefields are extrapolated upwards in small steps, and an imaging condition [5,6,17,21,22] is applied at every step in order to recover the modeled 3D sea surface. The depth positions of the maximum image values define the sea surface.…”