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A. Flores-Orozco, A. Kemna, E. Zimmermann:
"Data error quantification in spectral induced polarization imaging";
Geophysics, 77(3) (2012), S. 227 - 237.

Induced polarization (IP) imaging is being increasingly used in near-surface geophysical studies, particularly for hydrogeologic and environmental applications. However, the analysis of IP data error has received little attention, even though the importance of an adequate error parameterization has been demonstrated for electrical resistivity imaging. Based on the analysis of data sets measured in the frequency range from 1 Hz to 1 kHz, we proposed a model for the quantification of phase data errors in IP measurements. The analyzed data sets were collected on an experimental tank containing targets of different polarizability. Our study is based on the common practice that the discrepancy of measurements taken in normal and reciprocal configuration can be considered as a measure of data error. Statistical analysis of the discrepancies between normal and reciprocal measurements revealed that the phase error decreases with increasing resistance (i.e., signal strength). We proposed an inverse power-law model to quantify the phase error as a function of the measured resistances. We found that the adequate implementation of the proposed error model in an inversion scheme leads to improved IP imaging results in laboratory experiments. Application to a data set collected at the field-scale also demonstrated the superiority of the new model over previous assumptions.