3-D inversion of induced polarization data

We develop three methods to invert induced polar-ization (IP) data. The foundation for our algorithms is an assumption that the ultimate effect of chargeability is to alter the effective conductivity when current is applied. This assumption, which was first put forth by Siegel and has been routinely adopted in the literature, permits the IP responses to be numerically modeled by carrying out two forward modelings using a DC resis-tivity algorithm. The intimate connection between DC and IP data means that inversion of IP data is a two-step process. First, the DC potentials are inverted to recover a background conductivity. The distribu-tion of chargeability can then be found by using any one of the three following techniques: (I) linearizing the IP data equation and solving a linear inverse problem, (2) manipulating the conductivities obtained after performing two DC resistivity inversions, and (3