Reciprocal error in Time Domain Induced Polarization: Systematic Noise or Systematic Signal?

Lore Vanhooren , Wouter Deleersnyder, Warre Dekoninck, Adrian Flores Orozco, Frédéric Nguyen, Corentin Caudron, Thomas Hermans 

Reciprocal measurements are standard for data quality control in electrical resistivity surveys, but their potential as an interpretation tool is rarely exploited. Under the assumption of linear subsurface behaviour, normal and reciprocal readings should yield the same results, but when a systematic offset is present it can be indicative for additional processes. Here we present a time-domain induced polarization (TDIP) dataset from a volcanic hydrothermal system (Reykjanes, Iceland) where a strong, systematic offset between normal and reciprocal measurements is observed. The discrepancy is present as a positive shift of the reciprocal decay curves (>100 mV/V). While both normal and reciprocal inversions resolve a strong IP anomaly in the southern part of the profile, a substantial offset exists between the two ( >20 mS/m). The offset is spatially confined and persistent over 100 consecutive days, the anomaly itself coincides with a strong IP response attributed to the mutual occurrence of clay minerals and disseminated iron sulphides and oxides. Besides random noise, we evaluate four possible mechanisms for the offset: (1) polarization of the electrodes, (2) inherent sensitivity differences between normal and reciprocal configurations, (3) stray currents from the nearby powerplant and (4) nonlinear IP effects where the response depends on the current density. Given the geological context and the localized nature of anomaly, a non-linear effect is plausible but the ambiguity between systematic noise and a genuine subsurface signal cannot be fully resolved with field data alone.
This study demonstrates that the systematic analysis of normal-reciprocal misfit in TDIP can serve as a widely accessible tool for identifying signals that, whether geologic, or anthropogenic in origin, are overlooked by standard data quality workflows.