Electromagnetic imaging is modelled as an inverse problem for the 3D system
of Maxwell's equations of which the isotropic conductivity distribution in
the domain of interest has to be reconstructed. The main application we ha
ve in mind is the monitoring of conducting contaminant plumes out of surfac
e and borehole electromagnetic imaging data. The essential feature of the m
ethod developed here is the use of adjoint fields for the reconstruction ta
sk, combined with a splitting of the data into smaller groups which define
subproblems of the inversion problem. The method works iteratively, and can
be considered as a nonlinear generalization of the algebraic reconstructio
n technique in x-ray tomography. Starting out from some initial guess for t
he conductivity distribution, an update for this guess is computed by solvi
ng one forward and one adjoint problem of the 3D Maxwell system at a time.
Numerical experiments are performed for a layered background medium in whic
h one or two localized (3D) inclusions are immersed. These have to be monit
ored out of surface to borehole and cross-borehole electromagnetic data. We
show that the algorithm is able to recover a single inclusion in the earth
which has high contrast to the background, and to distinguish between two
separated inclusions in the earth given certain borehole geometries.