• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.33-40
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• 2009

In field surveys using the dipole-dipole electrical resistivity method, we often encounter negative apparent resistivity. The term 'negative apparent resistivity' refers to apparent resistivity values with the opposite sign to surrounding data in a pseudosection. Because these negative apparent resistivity values have been regarded as measurement errors, we have discarded the negative apparent resistivity data. Some people have even used negative apparent resistivity data in an inversion process, by taking absolute values of the data. Our field experiments lead us to believe that the main cause for negative apparent resistivity is neither measurement errors nor the influence of self potentials. Furthermore, we also believe that it is not caused by the effects of induced polarization. One possible cause for negative apparent resistivity is the subsurface geological structure. In this study, we provide some numerical examples showing that negative apparent resistivity can arise from geological structures. In numerical examples, we simulate field data using a 3D numerical modelling algorithm, and then extract 2D sections. Our numerical experiments demonstrate that the negative apparent resistivity can be caused by geological structures modelled by U-shaped and crescent-shaped conductive models. Negative apparent resistivity usually occurs when potentials increase with distance from the current electrodes. By plotting the voltage-electrode position curves, we could confirm that when the voltage curves intersect each other, negative apparent resistivity appears. These numerical examples suggest that when we observe negative apparent resistivity in field surveys, we should consider the possibility that the negative apparent resistivity has been caused by geological structure.

• Geophysics and Geophysical Exploration
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• v.5 no.3
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• pp.199-205
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• 2002

In the resistivity method, the potential difference between two grounded electrodes is measured and this can be positive or negative. The apparent resistivity and the potential difference have the same polarity. Since the electric field is the gradient of the potential, the polarity of the potential difference depends on the direction of the electric field. If the direction of the vector connecting two grounded electrodes is the same to that of the electric field, the measured potential difference and the apparent resistivity become positive. If the opposite is the case, they become negative. In general, the primary electric field and the vector connecting two potential electrodes have the same direction in a surface resistivity method. In this case, the measured potential difference is always positive because the primary electric field is greater than the secondary field. Therefore, the apparent resistivity is always positive if noise is free and topography is flat. The secondary field component, however, can be greater than the primary field component along the vector connecting two potential electrodes in the cross-hole resistivity method. Furthermore, if the secondary electric field and the vector connecting two potential electrodes have an opposite direction, the apparent resistivity become negative. Consequently, the apparent resistivity may be negative in the region where the primary electric field component along the vector connecting two potential electrodes is very small.

• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.83-86
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• 2006

From numerical modeling test $-{\rho}a$ by one steel casing borehole near resistivity survey line can be acquired. Negative apparent resistivities even in the flat area are surely subsurface information. Inversion technique for those need to be developed in the near future.

• Geophysics and Geophysical Exploration
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• v.6 no.4
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• pp.165-170
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• 2003

Recently, resistivity surveys have been frequently carried out over the irregular terrain such as mountainous area. Such an irregular terrain itself can produce significant anomalies which may lead to misinterpretations. In this study, topographic effects in resistivity survey were studied using the physical scale modeling as well as the numerical one adopting finite element method. The scale modeling was conducted at a pond, so that we could avoid the edge effect, the inherent problem of the scale modeling conducted in a water tank in laboratory. The modeling experiments for two topographic features, a ridge and a valley with various slope angles, confirmed that the results by the two different modeling techniques coincide with each other fairly well for all the terrain models. These experiments adopting dipole-dipole array showed the distinctive terrain effects, such that a ridge produces a high apparent resistivity anomaly at the ridge center flanked by zones of lower apparent resistivity. On the other hand, a valley produces the opposite anomaly pattern, a central low flanked by highs. As the slope of a terrain model becomes steeper, the terrain-induced anomalies become stronger, and moreover, apparent resistivity can become even negative for the model with extremely high slope angle. All the modeling results led us to the conclusion that terrain effects should be included in the numerical modeling and/or the inversion process to interpret data acquired at the rugged terrain area.

• Geophysics and Geophysical Exploration
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• v.13 no.1
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• pp.128-131
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• 2010

• Geophysics and Geophysical Exploration
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• v.24 no.4
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• pp.171-179
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• 2021

We outline a process for estimating Cole-Cole parameters from time-domain induced polarization (IP) data. The IP transients are all inverted to 2D Cole-Cole earth models that include resistivity, chargeability, relaxation time, and the frequency exponent. Our inversion algorithm consists of two stages. We first convert the measured voltage decay curves into time series of current-on time apparent resistivity to circumvent the negative chargeability problem. As a first step, a 4D inversion recovers the resistivity model at each time channel that increases monotonically with time. The desired intrinsic Cole-Cole parameters are then recovered by inverting the resistivity time series of each inversion block. In the second step, the Cole-Cole parameters can be estimated readily by setting the initial model close to the true value through a grid search method. Finally, through inversion procedures applied to synthetic data sets, we demonstrate that our algorithm can image the Cole-Cole earth models effectively.