Seismic survey design methods often rely on qualitative measures to provide an optimal image of their objective target. Fold, ray tracing techniques counting ray hits on binned interfaces, and even advanced 3-D survey design methods that try to optimize o?set and azimuth coverage are prone to fail (especially in complex geological or structural settings) in their imaging predictions. The reason for the potential failure of these commonly used approaches derives from the fact that they do not take into account the ray geometry at the target points. Inverse theory results can provide quantitative and objective constraints on acquisition design. Beylkin??s contribution to this ?eld is an elegant and simple equation describing a reconstructed point scatterer given the source/receiver distribution used in the imaging experiment. Quantitative measures of spatial image resolution were developed to assess the e?cacy of competing acquisition geometries. Apart from the source/receiver con?guration, parameters such as the structure and seismic velocity also in?uence image resolution. Understanding their e?ect on image quality, allows us to better interpret the resolution results for the surveys under examination. A salt model was used to simulate imaging of target points located underneath and near the ?anks of the diapir. Three di?erent survey designs were examined. Results from these simulations show that contrary to simple models, near-o?sets do not always produce better resolved images than far-o?sets. However, consideration of decreasing signal-to-noise ratio revealed that images obtained from the far-o?set experiment are degrading faster than the near-o?set ones. The image analysis was performed on VSP ?eld data as well as synthetics generated by ?nite di?erence forward modeling. The predicted image resolution results were compared to measured resolution from the migrated sections of both the ?eld data and the synthetics. This comparison con?rms that image resolution analysis provides as good a resolution prediction as the prestack Kirchho? depth migrated section of the synthetic gathers. Even in the case of the migrated ?eld data, despite the presence of error introducing factors (di?erent signal-to-noise ratios, shape and frequency content of source wavelets, etc.), image resolution performed well exhibiting the same trends of resolution changes at di?erent test points.

Seismic survey design methods often rely on qualitative measures to provide an optimal image of their objective target. Fold, ray tracing techniques counting ray hits on binned interfaces, and even advanced 3-D survey design methods that try to optimize o?set and azimuth coverage are prone to fail (especially in complex geological or structural settings) in their imaging predictions. The reason for the potential failure of these commonly used approaches derives from the fact that they do not take into account the ray geometry at the target points. Inverse theory results can provide quantitative and objective constraints on acquisition design. Beylkin??s contribution to this ?eld is an elegant and simple equation describing a reconstructed point scatterer given the source/receiver distribution used in the imaging experiment. Quantitative measures of spatial image resolution were developed to assess the e?cacy of competing acquisition geometries. Apart from the source/receiver con?guration, parameters such as the structure and seismic velocity also in?uence image resolution. Understanding their e?ect on image quality, allows us to better interpret the resolution results for the surveys under examination. A salt model was used to simulate imaging of target points located underneath and near the ?anks of the diapir. Three di?erent survey designs were examined. Results from these simulations show that contrary to simple models, near-o?sets do not always produce better resolved images than far-o?sets. However, consideration of decreasing signal-to-noise ratio revealed that images obtained from the far-o?set experiment are degrading faster than the near-o?set ones. The image analysis was performed on VSP ?eld data as well as synthetics generated by ?nite di?erence forward modeling. The predicted image resolution results were compared to measured resolution from the migrated sections of both the ?eld data and the synthetics. This comparison con?rms that image resolution analysis provides as good a resolution prediction as the prestack Kirchho? depth migrated section of the synthetic gathers. Even in the case of the migrated ?eld data, despite the presence of error introducing factors (di?erent signal-to-noise ratios, shape and frequency content of source wavelets, etc.), image resolution performed well exhibiting the same trends of resolution changes at di?erent test points.