We use split Bregman and proximity operators to formulate geophysical inverse problems in a convex optimization setting.

A general data misfit term is considered to incorporate more realistic error probability assumptions than the ordinary Gaussian distribution.

Furthermore, we consider convex non-quadratic and non-smooth regularization terms as a prior information.

Linear and non-linear seismic travel-time tomography, are studied to evaluate the efficiency of the proposed formulation.