Год издания: 2024

This study investigates the challenges of imaging deep subsurface targets below complex near surface, described as random clutter. Our synthetic example, designed to simulate random clutter, reveals significant scattering distortions and defocusing effects, similar to those observed in complex field seismic data. We explore the use of statistical imaging through path summation as a heuristic method for achieving subsurface imaging without the need for an accurate velocity-depth model. This method utilizes an ensemble of random near-surface models that reflect the statistical complexity of the actual near-surface, without individually replicating the exact conditions. A statistical image is produced by summing the images obtained from the ensemble. We show that image traces undergo symmetric phase perturbations, which cancel out during the summation process, thus emphasizing true geological interfaces, albeit with a slight attenuation of higher frequencies. We establish an important connection between statistical imaging with small-scale heterogeneity and speckle scattering noise, highlighting the relationship between statistical imaging, small-scale heterogeneity, and speckle noise.