Soufi, Y ., Riahi, M.A. and Heidari, R., 2023. On the performance of Tikhonov, total variation and balanced Tikhonov-Total Variation regularizations in nonlinear seismic cross-hole tomography. Journal of Seismic Exploration, 32: 479-506. The ill-posed nature of geophysical problems requires the incorporation of an appropriate regularization function into the associated optimization framework. Usually, the choice of the regularization function depends on prior information about the properties of the unknown model parameters. As a conventional regularization function, Tikhonov regularization fails when reconstructing models with sharp discontinuities. In contrast, the first-order total variation regularization (TV) can reconstruct sharp edges or models with block-like features. Neither of these regularizations can reconstruct models with complex geometry that has both smooth and blocky features. In this study, we investigate different regularization functions for nonlinear seismic travel-time (cross- hole) tomography, where the model parameter is slowness. We use the alternating direction method of multipliers (ADMM) to solve the optimization with TV regularization. Also, a balanced combination of Tikhonov-TV regularizations in either its conventional form or new version with automatic balancing parameter is proposed for the nonlinear traveltime inversion. Using synthetic examples, we first show the robustness of the TV regularization solved by ADMM and also the good performance of the Tikhonov-TV regularization in recovering models with smooth blocky structures.