scholarly journals Application of electric polarization to contaminant detection in soils

1989 ◽  
Vol 26 (4) ◽  
pp. 536-550 ◽  
Author(s):  
Raymond N. Yong ◽  
Edward J. Hoppe
Keyword(s):  
Contaminant Transport ◽  
Time Domain ◽  
Mineral Exploration ◽  
Electric Polarization ◽  
Induced Polarization ◽  
Time Domain Reflectometry ◽  
Dielectric Measurements ◽  
Polarization Method ◽  
Contaminant Detection ◽  
Nonpolar Liquids

Preliminary experiments indicate the feasibility of constructing for field use a contaminant-detection instrumentation based on dielectric measurements. This study applies the technique of time-domain reflectometry to assess characteristic "signatures" of some selected contaminants and soil–contaminant mixtures. The results imply that a proper differentiation between various signatures can be attained, allowing an assessment in regard to soil–contaminant status. The proposed technique is similar in principle to the induced-polarization method applied in mineral exploration. Key words: electric polarization, contaminant transport, dielectrics, induced polarization, nonpolar liquids, time-domain reflectometry, relaxation, contaminant–soil interaction.

Time-domain-induced polarization: Full-decay forward modeling and 1D laterally constrained inversion of Cole-Cole parameters

Geophysics ◽  
2012 ◽  
Vol 77 (3) ◽  
pp. E213-E225 ◽  
Author(s):  
Gianluca Fiandaca ◽  
Esben Auken ◽  
Anders Vest Christiansen ◽  
Aurélie Gazoty
Keyword(s):  
Time Domain ◽  
Mineral Exploration ◽  
Induced Polarization ◽  
Significant Loss ◽  
Step Response ◽  
Model Parameters ◽  
Full Time ◽  
Inversion Algorithm ◽  
Modeling Tools ◽  
Polarization Response

Time-domain-induced polarization has significantly broadened its field of reference during the last decade, from mineral exploration to environmental geophysics, e.g., for clay and peat identification and landfill characterization. Though, insufficient modeling tools have hitherto limited the use of time-domain-induced polarization for wider purposes. For these reasons, a new forward code and inversion algorithm have been developed using the full-time decay of the induced polarization response, together with an accurate description of the transmitter waveform and of the receiver transfer function, to reconstruct the distribution of the Cole-Cole parameters of the earth. The accurate modeling of the transmitter waveform had a strong influence on the forward response, and we showed that the difference between a solution using a step response and a solution using the accurate modeling often is above 100%. Furthermore, the presence of low-pass filters in time-domain-induced polarization instruments affects the early times of the acquired decays (typically up to 100 ms) and has to be modeled in the forward response to avoid significant loss of resolution. The developed forward code has been implemented in a 1D laterally constrained inversion algorithm that extracts the spectral content of the induced polarization phenomenon in terms of the Cole-Cole parameters. Synthetic examples and field examples from Denmark showed a significant improvement in the resolution of the parameters that control the induced polarization response when compared to traditional integral chargeability inversion. The quality of the inversion results has been assessed by a complete uncertainty analysis of the model parameters; furthermore, borehole information confirm the outcomes of the field interpretations. With this new accurate code in situ time-domain-induced polarization measurements give access to new applications in environmental and hydrogeophysical investigations, e.g., accurate landfill delineation or on the relation between Cole-Cole and hydraulic parameters.

A time-domain induced-polarization method for estimating permeability in a shaly sand reservoir

2006 ◽  
Vol 54 (5) ◽  
pp. 623-631 ◽  
Author(s):  
Maosong Tong ◽  
Li Li ◽  
Weinan Wang ◽  
Yizhong Jiang
Keyword(s):  
Time Domain ◽  
Induced Polarization ◽  
Polarization Method ◽  
Shaly Sand

scholarly journals Improved Data Preprocessing Algorithm for Time-Domain Induced Polarization Method with Digital Notch Filter

2016 ◽  
Vol 64 (6) ◽  
pp. 2264-2288 ◽  
Author(s):  
Shuang-Chao Ge ◽  
Ming Deng ◽  
Kai Chen ◽  
Bin Li ◽  
Yuan Li
Keyword(s):  
Time Domain ◽  
Notch Filter ◽  
Data Preprocessing ◽  
Induced Polarization ◽  
Polarization Method ◽  
Digital Notch Filter

Modeling induced polarization effects in helicopter time-domain electromagnetic data: Field case studies

Geophysics ◽  
2017 ◽  
Vol 82 (2) ◽  
pp. B49-B61 ◽  
Author(s):  
Vladislav Kaminski ◽  
Andrea Viezzoli
Keyword(s):  
Time Domain ◽  
Signal To Noise Ratio ◽  
Mineral Exploration ◽  
Induced Polarization ◽  
Electromagnetic Transients ◽  
Additional Information ◽  
Time Domain Electromagnetic ◽  
Airborne Electromagnetic ◽  
Cole Model ◽  
Inversion Techniques

Induced polarization (IP) effects are becoming more evident in time-domain helicopter airborne electromagnetic (AEM) data thanks to advances in instrumentation, mainly due to improvements in the signal-to-noise ratio and hence better data quality. Although the IP effects are often manifested as negative receiver voltage values, which are easy to detect, in some cases, IP effects can distort recovered transients in other ways so they may be less obvious and require careful data analysis and processing. These effects represent a challenge for modeling and inversion of the AEM data. For proper modeling of electromagnetic transients, the chargeability of the subsurface and other parameters describing the dispersion also need to be taken into consideration. We use the Cole-Cole model to characterize the dispersion and for modeling of the IP effects in field AEM data, collected by different airborne systems over different geologies and exploration targets, including examples from diamond, gold, and base metal exploration. We determined how multiparametric inversion techniques can simultaneously recover all four Cole-Cole parameters, including resistivity [Formula: see text], chargeability [Formula: see text], relaxation time [Formula: see text], and frequency parameter [Formula: see text]. The results obtained are in good agreement with the ancillary information available. Interpretation of the IP effects in AEM data is therefore seen by the authors as providing corrected electrical resistivity distributions, as well as additional information that could assist in mineral exploration.

Sign in / Sign up

Export Citation Format

Share Document