An 1,100 km2 400-fold seismic survey was acquired over some of the largest sand dunes in UAE in 2007. Large sand dunes generate many challenges for seismic processing due to the irregular data acquisition, large statics caused by the significant difference between the sand and sabkha velocities, and a massive amount of reverberation noise that hides the signal in the data.

Occidental and ADNOC Sour Gas reprocessed this survey from January 2019 to August 2020 to overcome the challenges of the strong sand dune noise. For the first time, it was processed through prestack depth migration (PSDM). The primary objectives of the reprocessing project were to get an accurate PSDM volume that tied all of the available well control data; and to derive as accurate seismic amplitudes as possible over the target reservoir interval from near to far offsets to enable elastic inversion for reservoir porosity and net-thickness prediction.

Whilst the reprocessing project achieved the project objectives and generated good subsurface images, it did not run as smoothly as hoped, despite being processed by one of the premier multinational processing companies. The extremely large sand dunes, which are present across most of the survey area, created major imaging problems. Key technical lessons learnt during reprocessing included: (1) CRS errors occurred sporadically during acquisition, requiring correction; (2) the sand curve (Liner, 2008) worked well for sand dune static corrections for this data set; (3) near surface statics changed whilst the survey was acquired by up to 6 ms - each shot station needed to be corrected for these statics changes because the shot stations were acquired twice with a symmetric split recording spread; and (4) the contractor's standard post-migration processing sequence (gather flattening, radon, noise attenuation, stack) did not work well for this very noisy data set. Next time we work with similar data and require a high quality result, we know to double the estimated project timeline as every step in the processing sequence takes much longer than expected when the signal-to-noise ratio of the data is very low.

The novelty of this work was that we obtained large improvements in the seismic stack by applying offline gather conditioning before calculating trim statics to optimally flatten the very noisy migrated offset vector tile (OVT) gathers, prior to running the final noise attenuation and stacking workflows. Without this offline gather conditioning, the trim statics workflow mostly aligned the noise and damaged the stack.

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