Time-domain Induced Polarization Data Research Articles

Denoising time-domain induced polarisation data using wavelet techniques

Time-domain induced polarisation (TDIP) methods are routinely used for near-surface evaluations in quasi-urban environments harbouring networks of buried civil infrastructure. A conventional technique for improving signal to noise ratio in such environments is by using analogue or digital low-pass filtering followed by stacking and rectification. However, this induces large distortions in the processed data. In this study, we have conducted the first application of wavelet based denoising techniques for processing raw TDIP data. Our investigation included laboratory and field measurements to better understand the advantages and limitations of this technique. It was found that distortions arising from conventional filtering can be significantly avoided with the use of wavelet based denoising techniques. With recent advances in full-waveform acquisition and analysis, incorporation of wavelet denoising techniques can further enhance surveying capabilities. In this work, we present the rationale for utilising wavelet denoising methods and discuss some important implications, which can positively influence TDIP methods.

Hierarchical Bayesian method for mapping biogeochemical hot spots using induced polarization imaging

AbstractIn floodplain environments, a naturally reduced zone (NRZ) is considered to be a common biogeochemical hot spot, having distinct microbial and geochemical characteristics. Although important for understanding their role in mediating floodplain biogeochemical processes, mapping the subsurface distribution of NRZs over the dimensions of a floodplain is challenging, as conventional wellbore data are typically spatially limited and the distribution of NRZs is heterogeneous. In this study, we present an innovative methodology for the probabilistic mapping of NRZs within a three‐dimensional (3‐D) subsurface domain using induced polarization imaging, which is a noninvasive geophysical technique. Measurements consist of surface geophysical surveys and drilling‐recovered sediments at the U.S. Department of Energy field site near Rifle, CO (USA). Inversion of surface time domain‐induced polarization (TDIP) data yielded 3‐D images of the complex electrical resistivity, in terms of magnitude and phase, which are associated with mineral precipitation and other lithological properties. By extracting the TDIP data values colocated with wellbore lithological logs, we found that the NRZs have a different distribution of resistivity and polarization from the other aquifer sediments. To estimate the spatial distribution of NRZs, we developed a Bayesian hierarchical model to integrate the geophysical and wellbore data. In addition, the resistivity images were used to estimate hydrostratigraphic interfaces under the floodplain. Validation results showed that the integration of electrical imaging and wellbore data using a Bayesian hierarchical model was capable of mapping spatially heterogeneous interfaces and NRZ distributions thereby providing a minimally invasive means to parameterize a hydrobiogeochemical model of the floodplain.

Negative apparent chargeability in time-domain induced polarisation data

It appears to be relatively common to assume that negative apparent chargeability data in time-domain induced polarisation (IP) surveying is a sign of bad data quality. Negative IP data can however occur as a consequence of the distribution of chargeable zones in the ground, which is well documented in literature. A general mechanism behind negative IP data is proposed as follows; if the chargeable zones are mainly located in zones of negative sensitivity, and there is low or no chargeability in the positive sensitivity volumes in the investigated volume, it will result in negative apparent chargeability.Numerical modelling confirms that the phenomenon will typically occur for longer electrode separation if the chargeability is concentrated in a thin layer at the surface only, but that other distributions of the chargeable bodies can also cause negative IP data. Different electrode arrays differ in tendency to produce negative IP data, where dipole–dipole and pole–dipole arrays are more prone to generate negative data than nested arrays in the modelled examples. In addition to the relative location of the chargeable zone the resistivity is important for its impact on the apparent chargeability.Field data recorded in connection with the 3rd International IP Workshop on Ile d'Oléron in April 2014 confirm that negative apparent chargeability can be caused by a thin chargeable layer at the surface. The abundant negative IP data can be explained by an inverted model with low residuals, in which the chargeability is concentrated in a thin layer with modest chargeability close to the surface. Removing the data with negative apparent chargeability before inversion results in apparently poor resolution of the bottom layer and artefacts that are not present in the inversion results from the original data set. The results clearly demonstrate that negative apparent chargeability data can be a result of the distribution of chargeable zones in relation to the sensitivity distribution, and that such data should not be edited away on a routine basis since they contain important information.

An overview of a highly versatile forward and stable inverse algorithm for airborne, ground-based and borehole electromagnetic and electric data

We present an overview of a mature, robust and general algorithm providing a single framework for the inversion of most electromagnetic and electrical data types and instrument geometries. The implementation mainly uses a 1D earth formulation for electromagnetics and magnetic resonance sounding (MRS) responses, while the geoelectric responses are both 1D and 2D and the sheet’s response models a 3D conductive sheet in a conductive host with an overburden of varying thickness and resistivity. In all cases, the focus is placed on delivering full system forward modelling across all supported types of data. Our implementation is modular, meaning that the bulk of the algorithm is independent of data type, making it easy to add support for new types. Having implemented forward response routines and file I/O for a given data type provides access to a robust and general inversion engine. This engine includes support for mixed data types, arbitrary model parameter constraints, integration of prior information and calculation of both model parameter sensitivity analysis and depth of investigation. We present a review of our implementation and methodology and show four different examples illustrating the versatility of the algorithm. The first example is a laterally constrained joint inversion (LCI) of surface time domain induced polarisation (TDIP) data and borehole TDIP data. The second example shows a spatially constrained inversion (SCI) of airborne transient electromagnetic (AEM) data. The third example is an inversion and sensitivity analysis of MRS data, where the electrical structure is constrained with AEM data. The fourth example is an inversion of AEM data, where the model is described by a 3D sheet in a layered conductive host.

A time domain induced polarization relaxation time spectrum inversion method based on a damping factor and residual correction

Relaxation time spectra (RTS) derived from time domain induced polarization data (TDIP) are helpful to assess oil reservoir pore structures. However, due to the sensitivity to the signal-to-noise ratio (SNR), the inversion accuracy of the traditional singular value decomposition (SVD) inversion method reduces with a decrease of SNR. In order to enhance the inversion accuracy and improve robustness of the inversion method to the SNR, an improved inversion method, based on damping factor and spectrum component residual correction, is proposed in this study. The numerical inversion results show that the oscillation of the RTS derived from the SVD method increased with a decrease of SNR, which makes it impossible to get accurate inversion components. However, the SNR has little influence on inversion components of the improved method, and the RTS has high inversion accuracy and robustness. Moreover, RTS derived from core sample data is basically in accord with the pore-size distribution curve, and the RTS derived from the actual induced polarization logging data is smooth and continuous, which indicates that the improved method is practicable.

Resolving spectral information from time domain induced polarization data through 2-D inversion

SUMMARY Field-basedtimedomain(TD)inducedpolarization(IP)surveysareusuallymodelledbytaking into account only the integral chargeability, thus disregarding spectral content. Furthermore, the effect of the transmitted waveform is commonly neglected, biasing inversion results. Given these limitations of conventional approaches, a new 2-D inversion algorithm has been developed using the full voltage decay of the IP response, together with an accurate description of the transmitter waveform and receiver transfer function. This allows reconstruction of the spectral information contained in the TD decay series. The inversion algorithm is based around a 2-D complex conductivity kernel that is computedoverarangeoffrequenciesandconvertedtotheTDthroughafastHankeltransform. Two key points in the implementation ensure that computation times are minimized. First, the speed of the Jacobian computation, time transformed from frequency domain through the same transformation adopted for the forward response is optimized. Secondly, the reduction of the number of frequencies where the forward response and Jacobian are calculated: cubic splines are used to interpolate the responses to the frequency sampling necessary in the fast Hankel transform. These features, together with parallel computation, ensure inversion times comparable with those of direct current algorithms. Thealgorithmhasbeendevelopedinalaterallyconstrainedinversionscheme,andhandles both smooth and layered inversions; the latter being helpful in sedimentary environments, where quasi-layered models often represent the actual geology more accurately than smooth minimum-structure models. In the layered inversion approach, a general method to derive the thickness derivative from the complex conductivity Jacobian is also proposed. One synthetic example of layered inversion and one field example of smooth inversion show the capability of the algorithm and illustrates a complete uncertainty analysis of the model parameters. With this new algorithm, in situ TD IP measurements give access to the spectral content of the polarization processes, opening up new applications in environmental and hydrogeophysical investigations.

Application of time domain induced polarization to the mapping of lithotypes in a landfill site

Abstract. A direct current (DC) resistivity and time domain induced polarization (TDIP) survey was undertaken at a decommissioned landfill site situated in Hørløkke, Denmark, for the purpose of mapping the waste deposits and to discriminate important geological units that control the hydrology of the surrounding area. It is known that both waste deposits and clay have clear signatures in TDIP data, making it possible to enhance the resolution of geological structures compared to DC surveys alone. Four DC/TDIP profiles were carried out crossing the landfill, and another seven profiles in the surroundings provide a sufficiently dense coverage of the entire area. The whole dataset was inverted using a 1-D laterally constrained inversion scheme, recently implemented for TDIP data, in order to use the entire decay curves for reconstructing the electrical parameters of the soil in terms of the Cole-Cole polarization model. Results show that it is possible to resolve both the geometry of the buried waste body and key geological structures. In particular, it was possible to find a silt/clay lens at depth that correlates with the flow direction of the pollution plume spreading out from the landfill and to map a shallow sandy layer rich in clay that likely has a strong influence on the hydrology of the site. This interpretation of the geophysical findings was constrained by borehole data, in terms of geology and gamma ray logging. The results of this study are important for the impact of the resolved geological units on the hydrology of the area, making it possible to construct more realistic scenarios of the variation of the pollution plume as a function of the climate change.

Data processing method developments using TAU-transformation of Time-Domain IP data II. Interpretation results of field measured data

The paper presents field results of the data processing method developments based on approximate TAU-transform of the Time-Domain IP (Induced Polarization) curves. The theoretical basis of these developments was published in Part I by Turai and Dobróka (2011).Two ways for estimation of the type and the value of soil contaminations will be introduced. On first way the calculation of contamination type comes from the time constant value of the time constant spectra. The value estimation of the soil contamination is based on the Weighted Amplitude Value (WAV) of the time constant spectra. On second way we define the corrected apparent conductivity of the contaminated material (σcorr) as a product of time-constant spectrum and measured apparent conductivity. The σcorr parameter is useful for classification of contamination level.These methods were tested over several contaminated area (Offheim — 1992, Nyékládháza — 1997–2008, Ráckeve — 1997, Kecskemét — 1997, Győröcske — 1999, Pásztó — 2000, Tokaj — 2001, Balmazújváros — 2002, Szerencs — 2004, Tiszapalkonya —2004, Berekböszörmény —2007, Nagytárkány —2008, Darvastó — 2008, Miskolc-Hejőpart — 2008, Tiszavasvári — 2008, Nagytétény — 2008, Miskolc-Bedő hegy — 2009, Telkibánya — 2010, Miskolc-Salakbánya — 2010, Miskolc-Gózon L. út — 2010 and Miskolctapolca-Várhegy — 2010).Some results from interpreting field data collected over waste sites and other contaminated areas are presented. The contamination level and the main components of the contaminating material are characterized based on the time-constant spectra.

Relaxation time distribution from time domain induced polarization measurements

SUMMARY We propose an algorithm for inverting time domain induced polarization data to a relaxation time distribution. The algorithm is based on the (Tikhonov) regularized solution of the 2 nd kind Fredholm integral equation. We test the algorithm on synthetic data, and show its robustness for a noise level, typical of laboratory time domain measurements. We also show that, for the inversion purpose, the time domain data must be obtained with the different current wavelengths. We then test the algorithm on the experimental data recently obtained on brinesaturated medium-grained quartz sand (average grain diameter of 4 × 10 −4 m), and on sand mixtures. For the medium-grained sand, relaxation time distribution contains a main peak at 25 s. Different amounts (3%, 8% and 12%) of fine-grained quartz sand (average grain diameter of 1.12 × 10 −4 m) were added to the medium-grained quartz sand. For the sand mixture, an additional peak is observed in the relaxation time distributions, in the time range from 1.0 to 2.5 s. The magnitude of the second peak increases with the increase of the fine-grained sand content. Therefore, the experimental data show that peaks in the relaxation time distributions are related to the grain size. On the basis of the known peak location, and of the known grain size value, we obtained the values of the diffusion coefficient, which were found to be of the same order of magnitude as those in the bulk solution.

EM-coupling removal from time-domain IP data

Electromagnetic (EM) coupling of frequency-domain induced polarisation (IP) data has been the subject of many studies, and a number of ‘de-coupling’ procedures have been devised. However, there has been far less emphasis on coupling in the time domain, the normal approaches being to wait until late times and assume the EM contribution is insignificant or, less frequently, to invoke a Cole-Cole model to account for the EM-coupling response. A fast and simple procedure has been devised for suppression of EM-coupling effects in time-domain IP data. The essence of the approach is to represent the EM-coupling as a half-space decay. The half-space resistivity (EM apparent resistivity) is adjusted via inversion until the fit to the observed transient voltage decay is optimal in the least squares sense. The EM voltages associated with this best-fitting EM half-space decay are then subtracted from the measured voltages to yield a de-coupled ‘IP transient’. Transients that are well represented by an EM half-space decay are deemed ‘non-responsive’ in the context of IP. Transients that deviate markedly from an EM half-space decay are indicative of high apparent chargeability. The application of the new procedure is illustrated on dipole-dipole IP data from the Yandal greenstone belt of Western Australia.

Spectral Induced-Polarization Parameters As Determined Through Time-Domain Measurements

A method for the extraction of Cole?Cole spectral parameters from time-domain induced polarization data is demonstrated. The instrumentation required to effect the measurement and analysis is described. The Cole?Cole impedance model is shown to work equally well in the time domain as in the frequency domain. Field trials show the time-domain method to generate spectral parameters consistent with those generated by frequency-domain surveys. This is shown to be possible without significant alteration to field procedures. Cole?Cole time constants of up to 100 s are shown to be resolvable given a transmitted current of a 2 s pulse time. The process proves to have added usefulness as the Cole-Cole forward solution proves an excellent basis for quantifying noise in the measured decay.