Difficulties in processing land seismic data often arise due to insufficient sampling of the wavefield, resulting in poor near surface imaging, and aliasing of coherent noise forms such as surface waves. These problems can be mitigated by improving the wavefield sampling through denser acquisition. Fully unconstrained simultaneous shooting offers a way to substantially increase productivity and hence source densities. However, in order to achieve this we must be able to separate the signal from the interference noise generated by the blended acquisition. Using a de-blending routine based on inverse problems in the curvelet domain (Guillouet et al., 2016) the following case study from The Sultanate of Oman demonstrates the benefits of dense source sampling for broadband, wide-azimuth land data acquired using simultaneous shooting.


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