Eikonal-equation-based characteristic reflection traveltime tomography

Abstract

Automatically picking reflection traveltimes from the pre-stack shot gathers and positioning and updating the reflector depths during inversion are challenging in conventional Eikonal-equation-based adjoint state reflection traveltime tomography methods. To solve these problems, we propose an Eikonal-equation-based adjoint state characteristic reflection traveltime tomography (ASCRT) method. This method automatically extracts the reflection traveltimes by sequentially applying characteristic reflector picking in the depth migration section, Eikonal-equation-based traveltime calculation, and an event tracking algorithm. We also develop an efficient Eikonal-equation-based kinematic imaging method to rapidly position and update the reflector depths. With the proposed ASCRT method, the characteristic reflector positions and the velocity above the reflector are alternately updated. The proposed ASCRT method is performed with a layer-stripping strategy that sequentially uses selected characteristic reflectors to update the velocity model from shallow to deep. Compared to the wave-equation-based reflection traveltime inversion methods, the efficiency of the ASCRT method is improved by several orders of magnitude, and the memory consumption is remarkably reduced. Synthetic and field data examples are presented to show the effectiveness and efficiency of the proposed method.