• 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.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.4
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• pp.361-371
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• 2009

Resistivity tomography is very effective geophysical method to find out the resistivity distribution and its change in time around a tunnel. Thus, the resistivity tomogram can provide helpful information which is necessary for the effective maintenance of the tunnel. However, an air filled tunnel severely distorts tomography data, especially when the current or potential electrode is placed near the tunnel. Moreover, the distortion can often lead to misinterpretation of tomography monitoring data. To solve these problem, we developed a resistivity modeling and time-lapse inversion program which include a tunnel. In this study, using the developed program we assured that the inversion including a tunnel gives much more accurate image around a tunnel, compared with the conventional tomogram where the tunnel is not included. We also confirmed that the time-lapse inversion of resistivity monitoring data defines well resistivity changed areas around a tunnel in time.

• Geophysics and Geophysical Exploration
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• v.17 no.2
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• pp.104-113
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• 2014

Electric resistivity monitoring was applied to evaluate the soft ground in reclaimed land in order to figure out the applicability of physical prospecting. For this, electrical resistivity monitoring data were acquired for total three months and analyzed those data with independent inversion, time-lapse inversion, and 4D inversion methods. The result was compared for various inversion methods so as to figure out what showed the soft soil most properly. Moreover, drilling and CPT(Cone Penetration Test) data were also used in order to find out if each of those inversion methods could distinguish either bed rock or the soft soil clearly. And according to the result, time-lapse inversion showed less inversion artifacts than independent inversion, so it could indicate the soft soil better. If data gained for a longer period than three months are used, 4D inversion has been found to be a more efficient analysis method than the time-lapse inversion method. Electrical resistivity monitoring on the soft soil has been found to be a useful method that can analyze the spatio-temporal electric state of the ground serially.

• Geophysics and Geophysical Exploration
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• v.16 no.4
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• pp.217-224
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• 2013

We developed a time-lapse inversion using new cross-model constraints based on change ratio and resolution of model parameters. The cross-model constraint based on change ratio imposes the same penalty on the model parameters with equal change ratio. This constraint can emphasize the model parameters with significant change regardless of their increase or decrease. The resolution cross-model constraint imposes a small penalty on the model parameters with poor resolution, but a large penalty on the model parameters with good resolution. Thus, the model parameter with poor resolution can be effectively identified in the inversion result if they are significantly changed with time. Through the numerical tests for 3D resistivity monitoring data sets, the performance of these two cross-model constraints was confirmed. Finally, for the safety estimation of a sea dyke, we applied the developed time-lapse inversion to the 3D resistivity monitoring data that were acquired at a sea dike located in western coastal area of Korea. The result of time-lapse inversion suggested that there were no significant changes at the sea dike during the monitoring period.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.139-149
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• 2018

The resistivity monitoring is a practical method to resolve changes in resistivity of underground structures over time. With the advance of sophisticated automatic data acquisition system and rapid data communication technology, resistivity monitoring has been widely applied to understand spatio-temporal changes of subsurface. In this study, a new 4D inversion algorithm is developed, which can effectively emphasize significant changes of underground resistivity with time. To overcome the overly smoothing problem in 4D inversion, the Lagrangian multipliers in the space-domain and time-domain are determined automatically so that the proportion of the model constraints to the misfit roughness remains constant throughout entire inversion process. Furthermore, a focusing model constraint is added to emphasize significant spatio-temporal changes. The performance of the developed algorithm is demonstrated by the numerical experiments using the synthetic data set for a time-lapse model.

• Geophysics and Geophysical Exploration
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• v.15 no.1
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• pp.33-38
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• 2012

A resistivity method has been applied to wide range of engineering and environmental problems with the help of automatic and precise data acquisition. Thus, more accurate modeling and inversion of time-lapse monitoring data are required since resistivity monitoring has been introduced to quantitatively find out subsurface changes With respect to time. Here, we used the finite element method (FEM) for 3D resistivity modeling since the method is easy to realize complex topography and arbitrary shaped anomalous bodies. In the FEM, the linear elements, also referred to as first order elements, have certain advantages of simple formulation and narrow bandwidth of system equation. However, the linear elements show the poor accuracy and slow convergence of the solution with respect to the number of elements or nodes. To achieve the higher accuracy of finite element solution, high order elements are generally used. In this study, we developed a 3D resistivity modeling program using high order Serendipity elements. Comparing the Serendipity element solutions for a cube model with the linear element solutions, we assured that the Serendipity element solutions are more accurate than the linear element solutions in the 3D resistivity modeling.