Comparative analysis of eikonal-based first-arrival tomography: A case study from the Santos Basin, Brazil

Abstract

We compare classical and adjoint-state first-arrival tomography approaches in subsurface model reconstruction, focusing on pre-salt updates with a circular-shot ocean bottom node geometry. The investigation demonstrates that, whereas conventional tomography has faster convergence and better alignment with observed data, it produces significant noise artefacts and fails to adequately represent the reservoir section. In contrast, adjoint-state tomography provides superior model reconstruction by taking into account the complete travel time volume, significantly lowering noise and boosting reservoir imaging despite its higher computational cost. A quantitative investigation of root mean squared errors for ultra-long offsets confirms the efficacy of adjoint-state tomography in minimizing data misfit and improving model fidelity. The findings emphasize the potential of adjoint-state tomography in enhancing subsurface imaging and underscore the limits of conventional tomography in handling complex subsurface details with sparse acquisition geometry.