Abstract

AbstractIn land acquisition, particularly in Western China, the near surface layer is often dominated by small‐scale heterogeneities. Strong scatterings generated in this layer can seriously affect the quality of data acquisition and depth imaging. Although it has drawn wide attention from the industry and research community, there is lack of an effective way to investigate the relation between the shallow heterogeneities and the quality of the depth image. In this paper, we introduce the parameterized random velocity model to simulate the velocity heterogeneities in the shallow depth, thus statistical parameters such as the random spectra, correlation length, root mean square velocity perturbation can be used to describe the highly complicated small‐scale heterogeneities. In the meantime, we introduce the point spreading function to investigate the image quality. The point spreading function and its amplitude and phase spectra in wavenumber domain provide useful information to characterize the quality of the image. This simplifies the descriptions for both complex shallow velocity models and distortions of depth image, making it possible to create a concise relationship between the two. We further use numerical calculations to correlate statistical parameters of random models with the characteristics of point spreading functions. In this way, the relationship between shallow heterogeneities and the depth image can be quantitatively investigated. The proposed method is validated by numerical examples. The results reveal that the thickness of the random layer, the root mean square velocity perturbation, and the correlation length all apparently affect the quality of the depth image.

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