• Geophysics and Geophysical Exploration
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• v.24 no.4
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• pp.139-148
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• 2021

Negative apparent chargeability data in time-domain induced polarization (IP) survey are very often considered as noise and rejected before the inversion stage. Negative IP data can, however, occur naturally as a consequence of the distribution of chargeable zones in the ground. In some cases, the negative apparent chargeability values may account for most of the data measured. Negative IP data are caused by the geometry of chargeable zones and electrode positions. Negative apparent chargeability data appear most frequently when a dipole-dipole array is used. In this study, the effect of negative apparent chargeability data on inversion results is analyzed through the numerical 2D time-domain IP modeling and nonlinear inversion. The results demonstrate clearly that negative apparent chargeability data have to be included in the inversion as they contain important information on the distribution of subsurface chargeability.

• Geophysics and Geophysical Exploration
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• v.24 no.4
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• pp.171-179
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• 2021

We outline a process for estimating Cole-Cole parameters from time-domain induced polarization (IP) data. The IP transients are all inverted to 2D Cole-Cole earth models that include resistivity, chargeability, relaxation time, and the frequency exponent. Our inversion algorithm consists of two stages. We first convert the measured voltage decay curves into time series of current-on time apparent resistivity to circumvent the negative chargeability problem. As a first step, a 4D inversion recovers the resistivity model at each time channel that increases monotonically with time. The desired intrinsic Cole-Cole parameters are then recovered by inverting the resistivity time series of each inversion block. In the second step, the Cole-Cole parameters can be estimated readily by setting the initial model close to the true value through a grid search method. Finally, through inversion procedures applied to synthetic data sets, we demonstrate that our algorithm can image the Cole-Cole earth models effectively.