• Geophysics and Geophysical Exploration
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• v.24 no.4
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• pp.149-157
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• 2021

Given that induced polarization (IP) and direct current (DC) resistivity surveys are similar in terms of data acquisition, most DC resistivity systems are equipped with a time-domain IP data acquisition function. In addition, the time-domain IP data include the DC resistivity values. As such, IP and DC resistivity data are intimately linked, and the inversion of IP data is a two-step process based on DC resistivity inversions. Nevertheless, IP surveys are rarely applied, in contrast to DC resistivity surveys, as proper inversion software is unavailable. In this study, through numerical modeling and inversion experiments, we analyze the problems with the conventional inverse mapping technique used to invert time-domain IP data. Furthermore, we propose a modified inverse mapping technique that can effectively suppress inversion artifacts. The performance of the technique is confirmed through inversions applied to synthetic IP data.

• The Journal of Engineering Geology
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• v.28 no.3
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• pp.367-377
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• 2018

This study introduces a DC resistivity inversion method that incorporates structural and inequality constraints to enhance the resolution of resistivity inversions, and presents sample inversion results with these constraints. In the constrained inversions, a base model is constructed from a layered model through interpretation of other geophysical data. Inversion tests establish that both the structural and inequality constraints produce better resistivity models than the unconstrained inversion. However, the inequality inversion not only reproduces the exact layered structure of the background, it reproduces conductive anomalies at a depth of ~ 10 m when an inexact base model of electrical resistivity is used.

• 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.

• Geophysics and Geophysical Exploration
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• v.24 no.4
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• pp.180-193
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• 2021

The complex resistivity method is an exploration technique that can obtain various characteristic information of underground media by measuring resistivity and phase in the frequency domain, and its utilization has recently increased. In this paper, a three-dimensional inversion algorithm for the CR data was developed to increase the utilization of this method. The Poisson equation, which can be applied when the electromagnetic coupling effect is ignored, was applied to the modeling, and the inversion algorithm was developed by modifying the existing algorithm by adopting comlex variables. In order to increase the stability of the inversion, a technique was introduced to automatically adjust the Lagrangian multiplier according to the ratio of the error vector and the model update vector. Furthermore, to compensate for the loss of data due to noisy phase data, a two-step inversion method that conducts inversion iterations using only resistivity data in the beginning and both of resistivity and phase data in the second half was developed. As a result of the experiment for the synthetic data, stable inversion results were obtained, and the validity to real data was also confirmed by applying the developed 3D inversion algorithm to the analysis of field data acquired near a hydrothermal mine.

• Geophysics and Geophysical Exploration
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• v.10 no.2
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• pp.138-146
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• 2007

This paper describes 2.5D induced polarization (IP) modeling and inversion algorithms using complex resistivity. The complex resistivity method has merits for acquiring more valuable information about hydraulic parameters and pore fluid than the conventional IP methods. The IP modeling and inversion algorithms are developed by allowing complex arithmetic in existing DC modeling and inversion algorithms. The IP modeling and inversion algorithms use a 2.5D DC finite-element algorithm and a damped least-squares method with smoothness constraints, respectively. The accuracy of the IP modeling algorithm is verified by comparing its responses of two synthetic models with two different approaches: linear filtering for a three-layer model and an integral equation method for a 3D model. Results from these methods are well matched to each other. The inversion algorithm is validated by a synthetic example which has two anomalous bodies, one is more conductive but non-polarizable than the background, and the other is polarizable but has the same resistivity as the background. From the inverted section, we can cleary identify each anomalous body with different locations. Furthermore, in order to verify its efficiency to the real filed example, we apply the inversion algorithm to another three-layer model which includes phase anomaly in the second layer.

• Geophysics and Geophysical Exploration
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• v.18 no.1
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• pp.14-20
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• 2015

Three-dimensional (3D) resistivity method is an effective tool in the engineering site survey because it can provide a 3D resistivity distribution of the site. In this study, we tried to find out faults, fractures and coal seams that can cause the collapse of the tunnel. We carried out 2D resistivity survey along 5 parallel lines and 11 cross lines and merged all the apparent resistivity data for 3D inversion. Finally, from the 3D resistivity image and drilling data we presented the 3D distribution of faults, fractures and coal seams that are considered the main cause of the tunnel collapse.

• The Journal of Engineering Geology
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• v.14 no.1
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• pp.21-28
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• 2004

Three-dimensional (3-D) resistivity inversion including a topographic effect can be considered theoretically to be the technique of acquiring the most accurate image in the interpretation of resistivity data, because it includes characteristic image that the actual subsurface structure is 3-D. In this study, a finite-element method was used as the numerical method in modeling, and the efficiency of Jacobian calculation has been maximized with sensitivity analysis for the destination block in inversion process. Also, during the iterative inversion, the resolution of inversion can be improved with the method of selecting the optimal value of Lagrange multiplier yielding minimum RMS(root mean square) error in the parabolic equation. In this paper, we present synthetic examples to compare the difference between the case which has the toprographic effect and the other case which has not the effect in the inversion process.

• Geophysics and Geophysical Exploration
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• v.22 no.3
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• pp.160-167
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• 2019

Resistivity inversion result may be distorted if the seepage line fluctuation within central core with the change of reservoir water level as well as the conductivity of the reservoir water is not taken into consideration because the reservoir dike is composed of three-dimensional (3D) resistivity structure. Consequently, to accurately analyze the resistivity changes inside the reservoir dike according to the change of reservoir water level, 3D electrical resistivity modeling for the 2D survey line considering topography and physical properties of dam components was carried out. In addition, 2D inversion was performed with the simulated 2D resistivity data for a given 3D model in order to compare it with the inversion result of real field data. For 283 reservoirs in Korea, 2D inversion results for the simulated 2D data and field 2D resistivity data were compared. Finally, the reservoirs with an inversion ratio of 50% or less were selected as reservoirs that require further precise investigation.

• 한국지구물리탐사학회:학술대회논문집
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• 2008.10a
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• pp.47-50
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• 2008

Streamer resistivity surveys in shallow marine environments were carried out to analyze sediment characteristics at the bottom of reservoir. Because the resistivity values of reservoir water are very low and those of sediment are relatively high, apparent resistivity values increase with depth. And it is necessary to eliminate the apparent resistivity data decreased highly when the number of separation increases. According to the repeated data processing, we proposed the resistivity ratio of upper-to-lower layer is $0.6{\sim}0.8$ because the RMS error of inversion leads to the minimum in these range. As a result of the inversion for two- and three-layer model, the inversion including water depth is proved to be more effective than conventional method.

• Geophysics and Geophysical Exploration
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• v.11 no.4
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• pp.326-334
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• 2008

The resistivity method has been used to image the electrical properties of the subsurface. Especially, this method has become suitable for monitoring since data could be rapidly and automatically acquired. In this study, we developed a time-lapse inversion algorithm for the interpretation of resistivity monitoring data. The developed inversion algorithm imposes a big penalty on the model parameter with small change, while a minimal penalty on the model parameter with large change compared to the reference model. Through the numerical experiments, we can ensure that the time-lapse inversion result shows more accurate and focused image where model parameters have changed. Also, applying the timelapse inversion method to the leakage detection of an embankment dam, we can confirm that there are three major leakage zones, but they have not changed over time.