In this case study we consider the seismic processing of a challenging land data set from the Arabian Peninsula. It suffers from rough top‐surface topography, a strongly varying weathering layer, and complex near‐surface geology. We aim at establishing a new seismic imaging workflow, well‐suited to these specific problems of land data processing. This workflow is based on the common‐reflection‐surface stack for topography, a generalized high‐density velocity analysis and stacking process. It is applied in a non‐interactive manner and provides an entire set of physically interpretable stacking parameters that include and complement the conventional stacking velocity. The implementation introduced combines two different approaches to topography handling to minimize the computational effort: after initial values of the stacking parameters are determined for a smoothly curved floating datum using conventional elevation statics, the final stack and also the related residual static correction are applied to the original prestack data, considering the true source and receiver elevations without the assumption of nearly vertical rays. Finally, we extrapolate all results to a chosen planar reference level using the stacking parameters. This redatuming procedure removes the influence of the rough measurement surface and provides standardized input for interpretation, tomographic velocity model determination, and post‐stack depth migration. The methodology of the residual static correction employed and the details of its application to this data example are discussed in a separate paper in this issue. In view of the complex near‐surface conditions, the imaging workflow that is conducted, i.e. stack – residual static correction – redatuming – tomographic inversion – prestack and post‐stack depth migration, leads to a significant improvement in resolution, signal‐to‐noise ratio and reflector continuity.

A B S T R A C TIn the case of onshore data sets, the acquired reflection events can be strongly impaired due to rough top-surface topography and inhomogeneities in the uppermost lowvelocity layer, the so-called weathering layer. Without accounting for these influences, the poor data quality will make data processing very difficult.Usually, the correction for the top-surface topography is not perfect. The residuals from this correction and the influence of the weathering layers lead to small distortions along the reflection events. We integrated a residual static correction method into our data-driven common-reflection-surface-stack-based imaging workflow to further eliminate such distortions. The moveout-corrected traces and the stacked pilot trace are cross-correlated to determine a final estimate of the surface-consistent residual statics in an iterative manner.As the handling of top-surface topography within the common-reflection-surface stack is discussed in a separate paper in this special issue, the corresponding residual static correction will be explained in more detail. For this purpose, the results obtained with a data set from the Arabian Peninsula will be presented.

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