DC resistivity and Induced Polarization (IP) surveys are commonly used in<br>engineering, ground water and environmental problems. The principle difficulty<br>arises with the interpretation of such data since neither the apparent resistivity<br>pseudosections nor the apparent chargeability pseudosections are adequate representations<br>of the subsurface structure. Such information can only be obtained<br>through rigorous inversion of the data. The solution for the distribution of electrical<br>conductivity that arises in a DC rtxistivity survey is a nonlinear inverse<br>problem. To solve this problem we discretize the earth into cells of constant conductivity<br>and then find a minimum structure model which adequately reproduces<br>the observations. This inversion is efficiently carried out using a generalized subspace<br>techniques so that the dimension of the matrix to be inverted is kept small.<br>The conductivity model obtained from inverting the DC resistivity data is used<br>as a background model for the inversion of IP data. The sensitivities from the<br>background conductivity provide a linear mapping between the apparent and intrinsic<br>chargeabilities. The intrinsic chargeability is therefore obtained by solving<br>a linear inverse problem. Again we use the subspace methodology but we also<br>impose the constraint that the intrinsic chargeability is positive. The inversion<br>algorithms are applied to synthetic and field data.


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