Offshore Abu Dhabi is characterized by ultra-shallow waters and thinly layered carbonate formations with high velocity and anisotropy contrasts. This produces complex recorded seismic wave-fields, riddled with noise and multiple energy, which are notoriously difficult to process. In a recent reprocessing project over a producing field offshore Abu Dhabi, we applied innovative processing techniques and obtained an unprecedented uplift in the final seismic image. 3D seismic data was acquired over the study area deploying airgun sources and 4-component receivers with ocean bottom cable (OBC) in an orthogonal cross-spread design. In vintage processing PZ summation was used to obtain the upgoing wavefield with the receiver ghost removed. 1D deconvolution was then applied to attenuate receiver-side pegleg multiples. Strong residual multiple energy nonetheless remained in the overburden and caused challenges in interpretation of the data. For the reprocessing, we applied a method known as up-down deconvolution, which is commonly used in deep water with a smooth water bottom. The implementation of up-down deconvolution in this ultrashallow water environment was challenging due to poor trace sampling and insufficient direct arrival energy in the shallow part of the recorded wavefield in the receiver domain. The mostly flat seafloor and horizontally stratified geology allowed us to implement the method in ultra-shallow water in the crossspread domain, with enhanced trace density. Further, we implemented a three-step method to model velocity and anisotropy parameters. We first used long offset seismic data to estimate effective velocity and anisotropy using a bi-spectral analysis method to pick non-hyperbolic moveout of the reflection data. Secondly, we independently measured Thomsen anisotropic parameters at seismic scale using available well logs and walk-away VSP data. These two independent methods provided an opportunity to build a simple layered anisotropy model. In the third step, we used reflection tomography to derive the final velocity and anisotropy models. The final model shows a wide variation of anisotropy within different geological layers of the survey area, where delta varies between -5% to 10% and epsilon varies between 0% to 40%. The shallow section exhibits high epsilon (30 to 40%) and negative delta values. The new seismic images provide a reliable interpretation of overburden structures. The Vertical Transverse isotropy (VTI) model shows consistency with sonic logs. The seismic images display high correlation with well synthetics at reservoir level. The reliability of the anisotropy model is confirmed by comparing a seismic structural depth map with well tops. The incorporation of anisotropy in incidence angle computation allows accurate angle stacks to be produced, which improves the reliability of subsequent AVO analysis. The workflow showcases the first successful implementation of up-down deconvolution in ultra-shallow waters to remove multiples, and reliable estimation of VTI parameters combining seismic and well data offshore Abu Dhabi.

Seismic processing is expected to deliver a reliable product for seismic structure interpretation and reservoir characterization to support subsequent reservoir modeling and drilling operation. 3D OBC wide-azimuth (WAZ) seismic data has a significant advantage in this respect, since it contains large offset and wide azimuth information, which can be utilized for amplitude versus offset (AVO) and amplitude versus azimuth (AVAz) analysis respectively. However, these advanced studies require area-specific data processing efforts in this region for strong linear noise, multiple noise, designature uncertainty etc. Seismic data re-processing was newly conducted in pre-stack time migration (PrSTM) sequence to overcome such technical challenges. Surface-wave noise attenuation was achieved by 2D and 3D model-based dispersive energy attenuation and multi-pass structure oriented filtering in pre-stack and post-stack stages. Source-side deghosting highlighted a low frequency residual bubble and was followed by another pass of de-bubbling based on a smooth spectrum assumption. Shallow water reverberation was minimized by 3D deconvolution and high-resolution radon demultiple. 5D regularization and interpolation with trace densification provided evenly populated traces for each angle and azimuth sectors. Intensive signal preservation protected diffraction energy and resulted in better fault imaging than the vintage processing outcome. Both the vintage and the re-processed seismic data were evaluated in quantitative manners to compare with each other. Angle stacks from the re-processing showed more reasonable response for AVO analysis. Azimuth stacks showed stable S/N ratio leading to higher confidence in azimuthal anisotropy analysis. All these seismic deliverables enable accurate elastic property estimation and detail fault interpreation at target reservoir intervals. The novelty of the proposed workflow is to overcome common technical problems with targeted noise and multiple reduction focusing on angle / azimuth stacks. It unlocks advanced geophysical study for carbonate reservoir in shallow water areas. Processing deliverables will be fully utilized in fault interpretation, AVO and AVAz analysis and will support the forthcoming field development activity.

Low fold poorly sampled vintage seismic data often suffers from poor fault imaging. This can have a critical impact on reserve estimation and well planning. Acquiring high density seismic data over producing fields requires overcoming logistic challenges along with additional costs and increased acquisition time. However, advances in seismic processing technology could improve the fault resolution of vintage seismic data in a cost effective manner. This has been proven in a case study from offshore Abu Dhabi. The presence of strong surface wave energy, resulting from the shallow water environment and near surface heterogeneity, masked events in the deeper part of the section. Poor and irregular spatial sampling caused aliasing of the surface wave. In the vintage processing, strong de-noising was applied to tackle the aliasing issue, which smeared the fault definitions. During the re-processing, a joint low-rank and sparse inversion was applied to regularize and densify the input data to obtain a de-aliased surface wave noise model. Subsequent adaptive subtraction of the noise from the input removed strong surface waves without damaging the body waves. The stack quality was improved by application of cascaded surface wave attenuation algorithms. Additional five dimensional Fourier reconstructions of the data improved the signal quality. A carefully designed fault-preserving residual noise attenuation workflow further reduced the residual noise content. Automatic picking of key stratigraphic horizons was carried out in order to evaluate the spatial resolution of the re-processing outcome. Sharper discontinuities along fault planes observed compared to the interpretation of the vintage seismic data. Increased confidence in fault interpretation is of value for structural restoration study and further reservoir understanding. In addition, several new, previously not-visible, small fault features were highlighted as evident from volumetric curvature and semblance analysis. They have been effectively utilized in a forthcoming drilling campaign to de-risk well operation. Multi-dimensional data densification to de-alias surface waves and five dimensional re-construction of the signal proved to be beneficial to enhance the fault features on the poorly sampled seismic data.

The lack of high-resolution subsurface images from poor seismic imaging quality leads to inaccurate AVO/AVAz analysis and fault interpretation, which are critical for reserves estimation and de-risking any imminent drilling decisions. In a developing filed, acquiring and processing a new seismic data often falls outside the time frame of ongoing field development, as it will require great efforts in overcoming logistics challenges along with additional costs. In this case study, in offshore Abu Dhabi, revisiting the vintage data with careful and detailed reprocessing whilst utilizing the latest technologies has proven to be an effective, practical and cost-efficient method in improving the fault resolution and reservoir characterization. In this case study, it is observed that the deeper events in the vintage data were masked by the strong surface wave energy. The irregular acquisition geometry of the seismic data caused the aliasing of the surface wave. The application of harsh de-noising techniques in the vintage processing further deteriorated the fault definition. Thus, to tackle the aliasing problem, 5D trace densification and regularization was applied to increase the input data and create a de-aliased surface wave model. This allowed for subsequent subtraction of the strong surface wave, without damaging the body wave. Further cascaded surface wave attenuation algorithm improved the image quality. Modern fault preserving residual noise attenuation was applied along with 5D Fourier reconstruction mitigated the residual noise content. It has been proven in the case study that multi-dimensional data densification and 5D reconstruction of the signal enhanced the fault delineation. By leveraging the modern signal-processing innovations, the final results produced a better overall reflection image focused on the angle/azimuth stacks suitable for fault interpretation, AVO and AVAz analysis. In conclusion, poorly vintage seismic data has been shown to possess a high value despite its irregular geometry and low resolution.

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