Suppression of surface-related and internal multiples is an outstanding challenge in seismic data processing. The former is particularly difficult in shallow water, whereas the latter is problematic for targets buried under complex, highly scattering overburdens. We propose a two-step, amplitude- and phase-preserving, inversion-based workflow, which addresses these problems. We apply Robust Estimation of Primaries by Sparse Inversion (R-EPSI) to suppress the surface-related multiples and solve for the source wavelet. A significant advantage of the inversion approach of the R-EPSI method is that it does not rely on an adaptive subtraction step that typically limits other de-multiple methods such as SRME. The resulting Green's function is used as input to a Marchenko equation-based approach to predict the complex interference pattern of all overburden-generated internal multiples at once, without a priori subsurface information. In theory, the interbed multiples can be predicted with correct amplitude and phase and, again, no adaptive filters are required. We illustrate this workflow by applying it on an Arabian Gulf field data example. It is crucial that all pre-processing steps are performed in an amplitude preserving way to restrict any impact on the accuracy of the multiple prediction. In practice, some minor inaccuracies in the processing flow may end up as prediction errors that need to be corrected for. Hence, we decided that the use of conservative adaptive filters is necessary to obtain the best results after interbed multiple removal. The obtained results show promising suppression of both surface-related and interbed multiples.
A B S T R A C TIn the past, integral formulations for marine data-driven demultiple methods have been derived from reciprocity theorems. Two fundamental assumptions in these derivations were that the sea-surface is flat and has a known reflection coefficient, often taken to be minus one. In this paper, we show that for dual sensor data these assumptions can be relaxed. The sea-surface has to obey the same conditions as any other reflecting boundary in the subsurface: it must be constant in time but shape and reflection strength can vary in space. For both surface-related multiple elimination, and multiple attenuation by multi-dimensional deconvolution, we derive integral equations that depend only on the measured pressure and particle velocity fields. Finally, we show there is an intimate connection between the integral equations for the methods.
I N T R O D U C T I O NIntegral equations for data-driven, multi-dimensional multiple attenuation can be derived from reciprocity theorems. The case of surface-related multiple elimination was derived by Fokkema and van den Berg (1993). Weglein et al. (2003) showed that for surface-related multiples the inverse scattering series approach, developed by Weglein et al. (1997), results in an equivalent integral formulation. Amundsen (2001) performed a similar derivation for multiple attenuation by multi-dimensional deconvolution.In all derivations, the boundary condition was that the seasurface is flat and that the pressure is zero at this surface. Berkhout and Verschuur (1997) derived a method to predict and subtract surface-related multiples through a feedback mechanism in which the sea-surface reflectivity can be parameterized. In practice, the surface-related multiples are subtracted in an adaptive way Verschuur and Berkhout (1997). In this paper, we reformulate surface-related multiple elimination and multi-dimensional deconvolution such that it can
The simultaneous firing of marine sources can provide a significant uplift in terms of acquisition efficiency and data quality enhancement. However, the seismic interference resulting from one or more ‘other’ sources needs to be well understood and the appropriate processing strategies need to be developed for the method to fulfil its promise.
In this paper, a modified inversion approach is presented for the effective separation of sources in marine simultaneous shooting acquisition. The method aims to distribute all energy in the simultaneous shot records by reconstructing the individual shot records at their respective locations. The method is applied to a wide azimuth data set acquired in the Gulf of Mexico where two sources out of four in total were fired simultaneously. Results demonstrate that the individual sources can be separated satisfactory, both at the prestack and post‐stack level.
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