scholarly journals Influence of Clay on Time Domain Induced Polarization

2018 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Yatini Yatini
Keyword(s):  
Time Domain ◽  
Physical Modeling ◽  
Mineral Exploration ◽  
Total Content ◽  
Spherical Model ◽  
Induced Polarization ◽  
Soil Medium ◽  
Spherical Target ◽  
Target Value ◽  
Modeling Data

The main problem in mineral exploration is how to determine the existence of deposits at subsurface based on resistivity and chargeability parameters. Clay almost exists in rocks. Here, this study was to understand the influence of clay on time domain induced polarization. To clarify the clay parameters, field physical modeling was conducted. The results showed physical modeling data of 20-cm diameter spherical target with a total content of 28.3% of iron did not show any significant response. The high content of clays on the medium used in field physical modeling seems to be the main reason for the change in sample. In the case of the subsurface spherical model that is near to the soil medium, the presence of clay leads to the medium resistivity value to be identical to the target value. As a consequence, the resistivity response can not be identified clearly. The chargeability between the medium and the target remains small but the chargeability response remains constant.

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.

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.

scholarly journals Physical Modeling on Time Domain Induced Polarization (TDIP) Response of Metal Mineral Content

2018 ◽  
Vol 8 (2) ◽  
pp. 57
Author(s):  
Yatini Yatini ◽  
Djoko Santoso ◽  
Agus Laesanpura ◽  
Budi Sulistijo
Keyword(s):  
Time Domain ◽  
Physical Modeling ◽  
Iron Ore ◽  
Mineral Content ◽  
Quantitative Relationship ◽  
Physical Modelling ◽  
Induced Polarization ◽  
Physical Models ◽  
Resistivity Method ◽  
The Relationship

The Induced Polarization (IP) methods is an extension of resistivity method by adding ability of the ground in storing electrical charge. One of the measurement technique is done in time domain, hereinafter referred to as Time Domain Induced Polarization (TDIP). TDIP responses measured on the surface are affected by the physical properties of the subsurface. Research in TDIP response modeling studies is performed to obtain a quantitative relationship between response to metallic mineral content at subsurface. The relationship can be obtained by forward and physical modelling. The forward modeling produces a curve that connects TDIP response to the subsurface parameters and an array. The laboratory-scale physical model is performed on the sand-box size (200x100x70) cm3 by varying iron-ore content in a sphere target. TDIP response measurements on physical models is done using Dipole-dipole and Wenner configuration. The relationship between the TDIP response and metal mineral content is obtained by comparing the results of measurements on physical modeling and forward modelling. There is good appropriatement between the theoretical curves and measuring results of the physical modelling. The greater of iron-ore content on the target, increasing in the TDIP response.

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.

Reliability of Time Domain Induced Polarization Data

2011 ◽  
Author(s):  
Aurélie Gazoty ◽  
Esben Auken ◽  
Jesper Pedersen ◽  
Gianluca Fiandaca ◽  
Anders Vest Christiansen
Keyword(s):  
Time Domain ◽  
Induced Polarization ◽  
Polarization Data
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