Near-surface imaging by enhancing the effect of internal multiples

A complex near surface is a large challenge in land seismic imaging due to its strong lateral heterogeneity. Furthermore, since the reflectors within the near-surface area are not always well measured, it is difficult to accurately estimate its velocity distribution of the subsurface. In this paper, we present a method to effectively exploit internal multiples in Joint Migration Inversion (JMI) for near-surface imaging. JMI is an inversion algorithm to automatically provide both velocity and reflectivity of the subsurface by utilizing primaries and all higher-order scattering. Our proposed method aims to improve the inverted velocity and reflectivity models through JMI by partially enhancing the residual between observed data and forward modeled data and suppressing the influence of diving waves and the insufficiently measured reflectors directly originating from the near-surface region. We give two numerical examples for synthetic models including a complex near-surface model to show the effectiveness of the proposed method.