An iterative Kalman filter-based method for traveltime tomography

Abstract

Abstract In addition to directly determining the inverted velocity, it is crucial to assess the uncertainty (or confidence) of the relevant velocity imaging results. This is especially true when dealing with time-lapse seismic data, which play a crucial role in detecting changes in fluid movement in petroleum reservoirs. In this study, we developed an iterative Kalman filter-based method to monitor time-lapse changes in the subsurface using traveltime tomography. Our approach considers the uncertainty of the results. We successfully verified the validity of our proposed method through synthetic crosshole and time-lapse tests. Our iterative Kalman filter-based method provides reasonable reconstruction results suitable for accessing uncertainties, and the algorithm can be used to monitor changes in the subsurface medium.