Investigating the resolution of IP arrays using inverse theory

Using a fast 2-D inverse solution, we examined the resolution of different resistivity/IP arrays using noisy synthetic data subject to minimum structure inversion. We compared estimated models from inversions of data from the dipole-dipole, pole-dipole, and pole-pole arrays over (1) a dipping, polarizable conductor, (2) two proximate conductive, polarizable bodies, (3) a polarizable conductor beneath conductive overburden, and (4) a thin, resistive, polarizable dike. The estimated resistivity and polarizability models obtained from inversion of the dipole-dipole data were usually similar to the pole-dipole estimated models. In the cases examined, the estimated models from the pole-pole data were more poorly resolved than the models from the other arrays. If pole-pole resistivity data contain even a fraction of a percent of Gaussian noise, the transformation of such data through superposition to equivalent data of other array types may be considerably distorted, and significant information can be lost using the pole-pole array. Though the gradient array is reputed to be more sensitive to dip than other arrays, it evidently contains little information on dip that does not also appear in dipole-dipole data, for joint inversion of dipole-dipole and gradient array data yields models virtually identical to those obtained from inversion of dipole-dipole data alone.