THEORY AND PRACTICE OF LOW‐FREQUENCY ELECTROMAGNETIC EXPLORATION

Geophysics ◽  
1948 ◽  
Vol 13 (4) ◽  
pp. 584-594 ◽  
Author(s):  
Haakon M. Evjen
Keyword(s):  
Dielectric Constant ◽  
Field Experiments ◽  
Low Frequency ◽  
Theory And Practice ◽  
Small Samples ◽  
Effective Dielectric Constant ◽  
Field Equations ◽  
First Approximation ◽  
Crystalline Salt ◽  
Simple Potential

Based directly on Maxwell’s Field Equations, the extremely low end of the frequency spectrum may be reduced in first approximation to simple potential theory. The approximation theory is borne out by some field experiments, the results of which are presented. Agreement with the theory, however, requires that the ground have a very large effective dielectric constant. This conclusion is supported by previous observations by a number of independent observers. Thus, the relaxation time has been found to be extremely great, not only in observations directly on the ground, but also in small samples of mud, and the sign of an electric anomaly over a relative insulator, such as crystalline salt or gas and oil, invariably has been found to be negative. Both of these observations can be explained in terms of a very great dielectric constant. The value yielded by the present experimental work is of the order of [Formula: see text].

Measurement of effective dielectric constant : A comparison

2011 ◽  
Author(s):  
Aakashdeep ◽  
Saurav Kr. Basu ◽  
G. V. Ujjwal ◽  
Sakshi Kumari ◽  
V. R. Gupta
Keyword(s):  
Dielectric Constant ◽  
Effective Dielectric Constant

Contributions to Silicon-Hydrogen Bond-Stretching Frequency in Amorphous Si Alloys

1992 ◽  
Vol 258 ◽  
Author(s):  
Z. Jing ◽  
J. L. Whitten ◽  
G. Lucovsky
Keyword(s):  
Experimental Data ◽  
Hydrogen Bond ◽  
Dielectric Constant ◽  
Ab Initio ◽  
Effective Dielectric Constant ◽  
Bond Energies ◽  
Calculated Frequency ◽  
Bond Stretching ◽  
Amorphous Si ◽  
Good Agreement

ABSTRACTWe have performed ab initio calculations and determined the bond-energies and vibrational frequencies of Si-H groups that are: i) attached to Si-atoms as their immediate, and also more distant neighbors; and ii) attached to three O-atoms as their immediate neighbors, but are connected to an all Si-atom matrix. These arrangements simulate bonding geometries on Si surfaces, and the calculated frequency for i) is in good agreement with that of an Si-H group on an Si surface. To compare these results with a-Si:H alloys it is necessary to take into account an additional factor: the effective dielectric constant of the host. We show how to do this, demonstrating the way results of the ab initio calculations should then be compared with experimental data.

scholarly journals Characterization of percolation behavior in conductor–dielectric 0-3 composites

2014 ◽  
Vol 04 (04) ◽  
pp. 1450035 ◽  
Author(s):  
Lin Zhang ◽  
Patrick Bass ◽  
Zhi-Min Dang ◽  
Z.-Y. Cheng
Keyword(s):  
Dielectric Constant ◽  
Percolation Threshold ◽  
Frequency Dependence ◽  
Experimental Results ◽  
Effective Dielectric Constant ◽  
Filler Concentration ◽  
Percolation Behavior ◽  
The Matrix ◽  
The Relationship

The equation ε eff ∝ (ϕc - ϕ)-s which shows the relationship between effective dielectric constant (εeff) and the filler concentration (φ), is widely used to determine the percolation behavior and obtain parameters, such as percolation threshold φc and the power constant s in conductor–dielectric composites (CDCs). Six different systems of CDCs were used to check the expression by fitting experimental results. It is found that the equation can fit the experimental results at any frequency. However, it is found that the fitting constants do not reflect the real percolation behavior of the composites. It is found that the dielectric constant is strongly dependent on the frequency, which is mainly due to the fact that the frequency dependence of the dielectric constant for the composites close to φc is almost independent of the matrix.

IP interpretation in environmental investigations

Geophysics ◽  
2002 ◽  
Vol 67 (1) ◽  
pp. 77-88 ◽  
Author(s):  
Lee D. Slater ◽  
David Lesmes
Keyword(s):  
Field Experiments ◽  
Low Frequency ◽  
Environmental Parameters ◽  
Clay Content ◽  
Chemistry Laboratory ◽  
Frequency Effect ◽  
Resistivity Method ◽  
Surface Polarization ◽  
Capacitive Properties ◽  
Diffusion Polarization

The induced polarization (IP) response of rocks and soils is a function of lithology and fluid conductivity. IP measurements are sensitive to the low‐frequency capacitive properties of rocks and soils, which are controlled by diffusion polarization mechanisms operating at the grain‐fluid interface. IP interpretation typically is in terms of the conventional field IP parameters: chargeability, percentage frequency effect, and phase angle. These parameters are dependent upon both surface polarization mechanisms and bulk (volumetric) conduction mechanisms. Consequently, they afford a poor quantification of surface polarization processes of interest to the field geophysicist. A parameter that quantifies the magnitude of surface polarization is the normalized chargeability, defined as the chargeability divided by the resistivity magnitude. This parameter is proportional to the quadrature conductivity measured in the complex resistivity method. For nonmetallic minerals, the quadrature conductivity and normalized chargeability are closely related to lithology (through the specific surface area) and surface chemistry. Laboratory and field experiments were performed to determine the dependence of the standard IP parameters and the normalized chargeability on two important environmental parameters: salinity and clay content. The laboratory experiments illustrate that the chargeability is strongly correlated with the sample resistivity, which depends on salinity, porosity, saturation, and clay content. The normalized chargeability is shown to be independent of the sample resistivity and it is proportional to the quadrature conductivity, which is directly related to the surface polarization processes. Laboratory‐derived relationships between conductivity and salinity, and normalized chargeability and clay content, are extended to the interpretation of 1‐D and 2‐D field‐IP surveys. In the 2‐D survey, the apparent conductivity and normalized chargeability data are used to segment the images into relatively clay‐free and clay‐rich zones. A similar approach can eventually be used to predict relative variations in the subsurface clay content, salinity and, perhaps, contaminant concentrations.

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