Inversion of 2.5D electrical resistivity data using the discrete adjoint method

Joint inversion of different geophysical data can impose different grid discretization constraints on the sought model parameters. We present a 2.5D inversion algorithm of electrical resistivity (ER) data that requires low memory storage and can handle fine discretization domains imposed by other geophysical (e. g, ground penetrating radar or seismic) data. This enables the ER data sensitivities to be directly joined with other geophysical data without the need of interpolating or coarsening the discretization. We employ the adjoint method directly in the discretized Maxwell's steady state equation and make no finite difference approximation on the Jacobian of the data. Our algorithm is tested on synthetic and field data acquired in a controlled alluvial aquifer.