We analyzed the feasibility of the common-reflection-surface (CRS) stack for near-surface surveys as an alternative to the conventional common midpoint (CMP) stacking procedure. The data-driven, less user-interactive CRS method could be more cost efficient for shallow surveys, where the high sensitivity to velocity analysis makes data processing a critical step. We compared the results for two field data sets collected to image shallow and ultrashallow reflectors: an example of shallow P-wave reflection for targets in the first few hundred meters, and an example of SH-wave reflection for targets in the first 10 m. By processing the shallow P-wave records using the CMP method, we imaged several nearly horizontal reflectors with onsets from 60 to about 250 ms. The CRS stack produced a stacked section more suited for a subsurface interpretation, without any preliminary formal and time-consuming velocity analysis, because the imaged reflectors possessed greater coherency and lateral continuity. With CMP processing of the SH-wave records, we imaged a dipping bedrock interface below four horizontal reflectors in unconsolidated, very low velocity sediments. The vertical and lateral resolution was very high, despite the very shallow depth: the image showed the pinchout of two layers at less than 10 m depth. The numerous traces used by the CRS stack improved the continuity of the shallowest reflector, but the deepest overburden reflectors appear unresolved, with not well-imaged pinchouts. Using the kinematic wavefield attributes determined for each stacking operation, we retrieved velocity fields fitting the stacking velocities we had estimated in the CMP processing. The use of CRS stack could be a significant step ahead to increase the acceptance of the seismic reflection method as a routine investigation method in shallow and ultrashallow seismics.

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.

In recent years, many case studies have demonstrated that the Common-Reflection-Surface (CRS) stack produces reliable stack sections with an excellent signal-to-noise ratio. In addition, an entire set of physically interpretable stacking parameters, so-called kinematic wavefield or CRS attributes, is determined. These attributes can be applied in further processing in such a way that a complete and consistent seismic reflection imaging workflow can be established which leads from the preprocessed multicoverage data in the time domain to migrated sections in the depth domain. The basic steps of this CRS-stack-based seismic reflection imaging workflow are the CRS stack itself, the determination of a smooth macrovelocity model by means of CRS attributes, and limited-aperture pre-and poststack Kirchhoff-type depth migration where the aperture is possibly optimized by means of the determined attributes. Our workflow approach has been applied to a recently acquired seismic dataset and revealed superior results compared to standard processing based on NMO/DMO/stack with a subsequent time migration and depth conversion.

GRIDA3 (Shared Resources Manager for Environmental Data Analysis and Applications) is a multidisciplinary project designed to deliver an integrated system to forge solutions to some environmental challenges such as the constant increase of polluted sites, the sustainability of natural resources usage and the forecast of extreme meteorological events. The GRIDA3 portal is mainly based on Web 2.0 technologies and EnginFrame framework. The portal, now at an advanced stage of development, provides end-users with intuitive Web-interfaces and tools that simplify job submission to the underneath computing resources. The framework manages the user authentication and authorization, then controls the action and job execution into the grid computing environment, collects the results and transforms them into an useful format on the client side. The GRIDA3 Portal framework will provide a problemsolving platform allowing, through appropriate access policies, the integration and the sharing of skills, resources and tools located at multiple sites across federated domains