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Ray-based seismic modeling methods can be applied at various stages of the exploration and production process. The standard ray method has several advantages, e.g., computational efficiency and the possibility of simulating propagation of elementary waves. As a high-frequency approximation, the method also has a number of limitations, particularly with respect to a lack of amplitude reliability in the presence of rapid changes of the model functions representing elastic parameters and interfaces. Given the objective of improving the applicability of the standard ray method, we present a strategy that does not require specific extension to finite frequencies. Instead, we define each ray-based process as an element of a system that, as a composite process, is able to obtain better results than the ray-based process applied alone. Other elements of the composite process can be finitedifference modeling or numerical solutions for surface and volume integrals, which are basic constituents of Kirchhoff modeling and imaging. We also include among the process elements recently developed techniques for simulating the migration amplitude on a target reflector and in a local volume, e.g., a reservoir zone. The model is decomposed according to its complexity into volume elements, surface elements, or a combination. The composite process consists of a specified interaction between process elements and model elements, which fits well with the philosophy of modern software design. Model elements that will be exposed to ray-tracing algorithms may need appropriate preparation, e.g., smoothing and resampling. We demonstrate specifically, in a tutorial example, that simulating the seismic response from a reflector by ray-based composite processes can yield better results than applying standard ray tracing alone.

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The sequestration of CO2 in subsurface reservoirs constitutes an immediate counter‐measure to reduce anthropogenic emissions of CO2, now recognized by international scientific panels to be the single most critical factor driving the observed global climatic warming. To ensure and verify the safe geological containment of CO2 underground, monitoring of the CO2 site is critical. In the high Arctic, environmental considerations are paramount and human impact through, for instance, active seismic surveys, has to be minimized. Efficient seismic modelling is a powerful tool to test the detectability and imaging capability prior to acquisition and thus improve the characterization of CO2 storage sites, taking both geological setting and seismic acquisition set‐up into account. The unique method presented here avoids the costly generation of large synthetic data sets by employing point spread functions to directly generate pre‐stack depth‐migrated seismic images. We test both a local‐target approach using an analytical filter assuming an average velocity and a full‐field approach accounting for the spatial variability of point spread functions. We assume a hypothetical CO2 plume emplaced in a sloping aquifer inspired by the conditions found at the University of Svalbard CO2 lab close to Longyearbyen, Svalbard, Norway, constituting an unconventional reservoir–cap rock system. Using the local‐target approach, we find that even the low‐to‐moderate values of porosity (5%–18%) measured in the reservoir should be sufficient to induce significant change in seismic response when CO2 is injected. The sensitivity of the seismic response to changes in CO2 saturation, however, is limited once a relatively low saturation threshold of 5% is exceeded. Depending on the illumination angle provided by the seismic survey, the quality of the images of five hypothetical CO2 plumes of varying volume differs depending on the steepness of their flanks. When comparing the resolution of two orthogonal 2D surveys to a 3D survey, we discover that the images of the 2D surveys contain significant artefacts, the CO2‐brine contact is misplaced and an additional reflector is introduced due to the projection of the point spread function of the unresolvable plane onto the imaging plane. All of these could easily lead to a misinterpretation of the behaviour of the injected CO2. Our workflow allows for testing the influence of geological heterogeneities in the target aquifer (igneous intrusions, faults, pervasive fracture networks) by utilizing increasingly complex and more realistic geological models as input as more information on the subsurface becomes available.

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