Wavefield-separation methods for dual-sensor towed-streamer data

Abstract

A dual-sensor towed streamer records the pressure and vertical component of particle motion associated with the incident wavefield that may be used to separate the wavefield into its upand downgoing parts. This procedure requires information about the water properties (wave-propagation velocity and density) and is robust in the presence of errors in the estimation of these quantities of the magnitude likely to be encountered. In practice, the particle motion data recorded by current towed marine streamers encounter very strong mechanical noise such that, for the lowest frequencies, the wavefield separation must be approximated by deconvolving the ghost function from the pressure data. This procedure requires information about the streamer depth and is robust to small depth errors over the frequency range for which it is required for dual-sensor streamer processing, but it is much more sensitive if applied over the bandwidth necessary to deghost pressure data acquired at a conventional streamer depth. The signal-to-noise ratio can be further enhanced by recombining the up-and downgoing pressure fields at the sea surface, which has the effect of applying a ghostlike filter to noise that is recorded by only one of the two sensors. In practical marine acquisition scenarios, spatial sampling is often insufficient to yield an accurate result, especially in the crossline direction. If each streamer is processed independently assuming that the wavefield propagation is purely inline, significant errors can be introduced. For arrivals with high emergent angles, errors may also be introduced even if the wavefield propagation actually is purely inline due to incorrect treatment of spatially aliased energy. However, these effects are almost entirely confined to very shallow events. They can be mitigated by using independently derived information about the crossline propagation angle and, for data comprising predominantly forward scattered energy, appropriate application of linear moveout.

Coherent noise suppression by learning and analyzing the morphology of the data

“…Denoising this frequency range is not in the scope of this work. The muted signal is generally retrieved using pressure measurements (Day et al, 2013). This shot gather is shown in Figure 8.…”

Bayesian seismic multi-scale inversion in complex Laplace mixed domains

“…So their solutions may become unstable or non-unique. Although there has been enormous development in seismic acquisition technology to achieve the acquisition of broadband seismic signals (Day et al 2013;Kroode et al 2013;Haavik and Landrø 2015), the signal-to-noise ratio (SNR) of low-and high-frequency components is also controversial topics, specifically for frequencies lower than 2-5 Hz and higher than 100 Hz. However, low frequencies play an important role in seismic exploration, especially for resolution enhancement, better imaging quality, effective inversion processes and direct fluid identification.…”

Variable source depth acquisition for improved marine broadband seismic data

“…The ghost reflections cause deep notches in the amplitude spectra of the recorded data at frequencies determined by the depths of the source and the receivers. Improvements in positioning systems, recording devices, computer power, and new processing algorithms are probably the most important factors that have made it possible to realize older ideas for dealing with the ghost (e.g., Berni, 1982;Ray and Moore, 1982;Sonneland and Berg, 1985). For the receiver side, broadband acquisition systems can be divided into two main categories: (1) multicomponent recordings (e.g., Loewenthal et al, 1985;Robertsson et al, 2008;Vaage et al, 2008;Day et al, 2013) and (2) slanted streamer profiles (e.g., Ray and Moore, 1982;Soubaras and Dowle, 2010;Seymour et al, 2012), which allows for deghosting by wavefield separation and deconvolution, respectively.…”

“…Improvements in positioning systems, recording devices, computer power, and new processing algorithms are probably the most important factors that have made it possible to realize older ideas for dealing with the ghost (e.g., Berni, 1982;Ray and Moore, 1982;Sonneland and Berg, 1985). For the receiver side, broadband acquisition systems can be divided into two main categories: (1) multicomponent recordings (e.g., Loewenthal et al, 1985;Robertsson et al, 2008;Vaage et al, 2008;Day et al, 2013) and (2) slanted streamer profiles (e.g., Ray and Moore, 1982;Soubaras and Dowle, 2010;Seymour et al, 2012), which allows for deghosting by wavefield separation and deconvolution, respectively. However, deghosting of conventional seismic data, i.e., pressure measurements at constant streamer depth, also result in improvements of the final image compared with nondeghosted data (Zhou et al, 2012;Dhelie et al, 2014).…”