Developing learned regularization for geophysical inversions

Geophysical inverse problems can be posed as the minimization of an objective function where one term (ϕ[sub d]) is a data misfit function and another (ϕ[sub m]) is a model regularization. In current practice, ϕ[sub m] is posed as a mathematical operator that potentially includes limited prior information on the model, m. This research focusses on the specification of learned forms of