A 2-DIMENSIONAL MAGNETOTELLURIC INVERSION ASSUMING GAUSSIAN STATIC SHIFT

A data-adaptive 2-D inversion scheme for magnetotelluric data, which s imultaneously finds the smoothest model with the smallest misfit whils t solving for galvanic static shift parameters, is described Trade-off parameters between data misfit, model roughness, and static shift nor m are determined so as to maximize the likelihood of the data on the a ssumption that static shifts have Gaussian distributions.