Plane-wave least-squares diffraction imaging using short-time singular spectrum analysis

Abstract Diffractions are seismic waves generated by small-scale heterogeneities in the subsurface. These often superimposed strong reflections so that they not visible on image, leading to misinterpretation and incorrect localization of scatterers. Therefore, separation diffracted reflected is a crucial step identifying these diffractors. To realize diffraction imaging, least-squares reverse time migration method plane (PLSRTM) optimized with short-time singular spectrum analysis (STSSA) was developed this work. The proposed STSSA algorithm exploits properties spectral (SSA) separate linear signals. By establishing Hanning window energy compensation function, it also compensates for shortcomings SSA local dip processing convergence As there no clear boundary between waves, loss during leads slow rate wave imaging technique. We use as constraint PLSRTM, which greatly improves quality waves. tests Sigsbee2A model noisy data have shown our can effectively improve resolution increases robustness data.