In marine geophysical exploration using seismic data, sea surface-related multiples can be used for imaging and producing extra illumination. However, the imaging of multiples can involve c...

Migration using sea surface-related multiples: Challenges and opportunitiesChallenges opportunities use multiples

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 have developed a two-step, amplitude- and phase-preserving, inversion-based workflow that addresses these problems. We apply robust estimation of primaries by sparse inversion (R-EPSI) to solve simultaneously for the surface-related primaries Green’s function and 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 demultiple methods such as surface-related multiple elimination. The resulting Green’s function is used as the input to a Marchenko equation-based approach to predict the complex interference pattern of all overburden-generated internal multiples at once. In this approach, no a priori information about the subsurface is needed. 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 preprocessing 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 for which corrections will be needed. Hence, we conclude that the use of conservative adaptive filters were necessary to obtain the best results after interbed multiple removal. The obtained results indicate promising suppression of surface-related and interbed multiples.

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Robust estimation of primaries by sparse inversion and Marchenko equation-based workflow for multiple suppression in the case of a shallow water layer and a complex overburden: A 2D case study in the Arabian Gulf

Optimizing measurement geometry for seismic near-surface full waveform inversion

During the past few years, significant improvements have been achieved in high-resolution imaging with seismic data. In particular, seismic full waveform inversion (FWI) has been proven to be a very promising tool. However, this technique requires high-quality data, whose acquisition can be very expensive. Furthermore, FWI is computationally extremely demanding, which currently limits its application to large-scale data sets. Both problems can be alleviated with optimized experimental design (OED) techniques. Using tools from the linearized inversion theory, we outline how source–receiver patterns can be identified that are most suitable for FWI experiments. This is demonstrated by reviewing a laboratory-scale experiment devoted to breast cancer detection with ultrasound data, and with a surface seismic survey study that is concerned with elastic FWI for shallow subsurface structures. By means of a vertical seismic profiling design example, we also show that the OED technology can be adapted to wavefield imaging techniques. Besides identifying optimized source–receiver patterns, OED can be employed for extracting the most useful attributes from a seismic data set, which can reduce the computational costs. For that purpose, we discuss a frequency-domain crosshole FWI experiment, where we quantify the information content of different data representations and identify suitable spatial and temporal sampling strategies. In a second crosshole study, it is inspected that source and receiver components allow the relevant elastic subsurface properties to be resolved. Finally, we outline a more general framework of seismic observables, with which the sensitivity of selected model parameters can be maximized. This is demonstrated with an example of regional earth mantle tomography.

Optimized Experimental Design in the Context of Seismic Full Waveform Inversion and Seismic Waveform Imaging

In the shallow water environment found in parts of the Barents Sea, conventional imaging struggles to provide good imaging of the near surface. This is due to the lack of near offsets (angles) in typical marine seismic data, caused by the large minimum distance between the source and receivers. Here, we present a method that uses separated (up- and down-going) wavefields provided by dual-sensor streamer technology to construct images and image gathers that span a complete range of incidence angles. In this method, each receiver is also used as a virtual source, hence providing a dataset that has complete coverage of zero- and near-offsets everywhere under the seismic spread. In particular, this provides near-angles for shallow targets that are not sampled by primaries, enabling amplitude versus angle (AVA) analysis to be carried out. The AVA results can be used as a direct hydrocarbon

Complete wavefield imaging for lithology and fluid prediction in the Barents Sea

Accurate sub-surface image reconstruction from prestack depth migration of surface seismic wavefields requires precise knowledge of the local propagation velocities between the recording location and the image location at depth. Such velocity information has traditionally been derived by tomographically inverting residual
moveout information of common image gathers, which have been computed using an initial velocity field. This methodology proves to be challenging in shallow water environments, particularly when strong and rapid velocity variations in the very shallow overburden need to be recovered, while moveout information from reflected arrivals is very sparse or not available.

High-fidelity complete wavefield velocity model building and imaging in shallow water environments - A North Sea case study

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High-fidelity complete wavefield velocity model building and imaging in shallow water environments - A North Sea case study