Doubling the spectrum of time-domain induced polarization by harmonic de-noising, drift correction, spike removal, tapered gating, and data uncertainty estimation

The extraction of spectral information in the inversion process of time-domain (TD) induced polarization (IP) data is changing the use of the TDIP method. Data interpretation is evolving from a qualitative description of the subsurface, able only to discriminate the presence of contrasts in chargeability parameters, towards a quantitative analysis of the investigated media, which allows for detailed soil- and rock-type characterization. Two major limitations restrict the extraction of the spectral information of TDIP data in the field: i) the difficulty of acquiring reliable early-time measurements, in the millisecond range and ii) the self-potential drift in the measured potentials distorting the shape of the late time IP responses, in the second range. Recent developments in TDIP acquisition equipment have given access to full waveform recordings of measured potentials and transmitted current, opening a breakthrough for data processing. For measuring at early times, we developed a new method for removing the significant noise from powerlines contained in the data through a model-based approach, localizing the fundamental frequency of the powerline signal in the full-waveform IP recordings. By this, we cancel both the fundamental signal and its harmonics. Furthermore, a novel and efficient processing scheme for identifying and removing spikes TDIP data is developed. The noise cancellation and the de-spiking allow the use of earlier and narrower gates, down to a few milliseconds after the current turn-off. Furthermore, tapered windows are used in the final gating of IP data, allowing the use of wider and overlapping gates for higher noise suppression without signal distortion. For measuring at late times, we have developed an algorithm for removal of the self-potential drift. Usually constant or linear drift-removal algorithms are used, but these algorithms fail in removing the background potentials due to the polarization of the electrodes previously used for current injection. We developed a drift-removal scheme that model the polarization effect and efficiently allows for preserving the shape of the IP responses at late times. Uncertainty estimates are essential in the inversion of IP data. Therefore, in the final step of the data processing, we estimate the data standard deviation based on the data variability within the IP gates and the misfit of the background drift removal Overall, the removal of harmonic noise, spikes, self-potential drift, tapered windowing and the uncertainty estimation allows for doubling the usable range of TDIP data to almost four decades in time (corresponding to four responses in frequency), and will significantly advance the science and the applicability of the IP method.