Preconditioned transmission + reflection joint traveltime tomography with adjoint‐state method for subsurface velocity model building

Abstract

Adjoint-state-based transmission and reflection traveltime inversion are promising approaches for reconstructing a macro velocity field in both shallow and deep depths. However, the contaminated gradient by the uneven illumination impedes the recovery of an optimal velocity model and results in slow convergence rate in inversion. To mitigate this issue, we propose a novel preconditioned transmission + reflection joint traveltime tomography method with transmission and reflection illumination compensation. The proposed illumination compensation operator is theoretically demonstrated as the diagonal elements of the approximated Hessian, which can be efficiently computed in a way similar to gradient calculation. The proposed method can construct a more accurate velocity model compared to the uncompensated counterpart. Convergence is also accelerated by the relatively uniform velocity updates from the shallow to the deep parts. Furthermore, velocity updating and reflector imaging are simultaneously iterated during the inversion. Synthetic numerical example based on the inclusion model indicates that the proposed preconditioned method can result in uniform gradient values of both transmitted and shot/receiver-side reflected traveltime. The complex foothill model test shows the improved inversion accuracy of the proposed method with an increased convergence rate and improved reflection traveltime predictions using the inverted velocity model. Experiment on the small foothill model indicates that the reflector and velocity can be updated simultaneously, and the inversion accuracy can be significantly improved by selecting multi reflectors. Finally, the effectiveness and practicality of the proposed method are demonstrated by a field data application in East China Sea.