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A high-resolution regional seismic, gravity and magnetics dataset was acquired offshore southern Gabon, which allowed an in-depth and integrated approach for analyzing the crustal setting in this area. Detailed analysis of the datasets available, and 3D modeling of the crust over this region, suggests that a more complex crustal setting than previously discussed in papers using either long offset 2D seismic, or detailed prospect scale 3D seismic datasets. Placing this information into the framework of the mega-regional publicly available gravity and magnetic datasets provides insights into the possible relationships between the changing upper and lower plate crustal settings experienced at different times in this area.

Most recent depth seismic imaging studies involve both full-wave and ray-based methods as the resolution of complex ill-posed problems often require a wide range of tools. Also ray based methods suffer from well-known drawbacks, they will provide accurate results in most of the cases. Moreover, relying on nonlinear slope tomography, a challenge-driven approach can be designed for each problem by incorporating prior or external information as needed. Here we propose to show such examples of the challenge-driven approach.

In previous publications, a hybrid deblending flow was proposed in which the last step of residual guided noise attenuation using the Noise to Signal Ratio (NSR) map was employed. This flow was proven to be effective and efficient for many OBS surveys. However, due to the more severe semi-coherent cross-talk noise in our data, a modification of the flow is needed. Utilizing the two insights (1) most recorded energy of the seismic data is bound within the direct arrival and shallow reflectors whose two-way-traveltime (TWT) is roughly known and (2) no or minimal remnant noise should be present in the extracted signal; we first focus on retrieving the direct arrival and primaries signals from shallow reflectors followed by retrieving the remaining primaries energy. Each iteration of signal inversion is accompanied by a three-dimensional joint low-rank and sparse inversion (JLSI) noise attenuation to ensure that minimal cross-talk noise would enter into the signal space.

A new non-linear tomographic inversion based method is put forward to resolve large velocity errors associated with complex geology which can cause poor imaging or migration artifacts. We propose to first create a series of trial-velocities from initial velocity by varying the values inside poor imaging zone. Migrations are followed using these trial velocities. The second stage involves CIG picking on these migrated gathers/stacks with tight constraint to ensure reliable picks. These CIG picks are then de-migrated to invariants with their corresponding trial velocities to form a set of invariants as the input to non-linear tomographic inversion.

A joint inversion of P-wave first arrivals, surface wave dispersion curves, and horizon picking of reflectivity image is proposed in order to produce a high resolution Vp (and Vs) model of the near-surface. These three datasets are merged together in a stochastic optimization process through a normalization taking into account of these different domains in the cost function. Resulting model is geologically consistent and reconcile wave velocities and the shallow reflectivity.

With many production reservoirs located at a depth greater than 1km, the near surface is often overlooked during seismic processing. Therefore, valuable information relating to shallow geohazards, faults and changes to lithology are lost or unused. We present a new processing methodology to improve the spatial resolution of the near-surface seismic image. The resulting seismic image has high spatial resolution making shallow features highly resolved. The derived velocity model is sufficiently highly resolved to be considered as a tool to aid in seismic interpretation and sediment classification. This comprehensive workflow was essential to overcome the challenges in shallow water acquisition.

The presence of absorption (Q) anomalies in the overburden, typically associated with gas accumulations, cause seismic obscured areas in our images and reduce our ability to see and interpret events inside the resulting “shadow zone”. In this paper we present our recent developments for addressing these challenges. We review progress made in the area of Q-compensating prestack depth migration (Q-PSDM) in order to deal with the co-existing multi-pathing and absorption effects for imaging through or under complex gas clouds using P-waves. In addition, to mitigate the problem associated with over-boosting of noise and migration artefacts introduced by Q-PSDM, more advanced imaging methods, such as least-squares Q-migration, have been developed to maximize the benefit of Q-PSDM. We then highlight a recently developed visco-acoustic full-waveform inversion (Q-FWI) model building technique for joint estimation of Q and velocity models. This has been applied to a production example from the Norwegian North Sea, where we see that the Q-FWI detects attenuating bodies of varying strength and scale throughout the survey and provides a clear uplift in the subsequent imaging process.

Reservoir imaging under the triangular Conger salt remains very challenging even after significant velocity model building efforts in recent years. Continuity and focusing of reservoir reflectors are sub-optimal due to the subtle velocity errors from the Conger salt and its neighboring carapace, which are very difficult for conventional methods, such as interpretation-guided salt scenarios and ray-based tomography, to resolve. Diving-wave full-waveform inversion (FWI) has difficulty updating the velocity at this depth due to the limit of maximum offset, and thus penetration depth, of input data. In this study, we performed reflection FWI (RFWI) using ocean-bottom node (OBN) data for velocity model updates. Our results showed that RFWI can effectively resolve the subtle low-wavenumber velocity errors in the overburden and substantially improve reservoir imaging. We also demonstrated that RFWI using OBN data can result in a better model than using wide-azimuth towed-streamer data due to its full azimuth and much longer offset coverage.

Reflection FWI is effective at providing low-wavenumber velocity updates for deep areas beyond the penetration depth of diving waves and significantly improves seismic imaging. However, the tomographic term of the FWI gradient that is good for low-wavenumber velocity updates can be contaminated by the much stronger high-wavenumber migration term. We present a reflection FWI workflow that is based on Born modeling and thus is free from the contamination of the migration term. In addition, we propose to use a set of partial stacks as reflectivity models for Born modeling to reduce the risks of cycle-skipping and incorrect update sign and to use a traveltime cost function to mitigate the negative impact from amplitude mismatch between input data and modeled synthetic data. Finally, we demonstrate the benefit and effectiveness of our approach using one field data set in the Gulf of Mexico.