• Journal of the Korean Geophysical Society
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• v.3 no.3
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• pp.161-174
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• 2000

Bayesian inversion is a stable approach to infer the subsurface structure with the limited data from geophysical explorations. In geophysical inverse process, due to the finite and discrete characteristics of field data and modeling process, some uncertainties are inherent and therefore probabilistic approach to the geophysical inversion is required. Bayesian framework provides theoretical base for the confidency and uncertainty analysis for the inference. However, most of the Bayesian inversion require the integration process of high dimension, so massive calculations like a Monte Carlo integration is demanded to solve it. This method, though, seemed suitable to apply to the geophysical problems which have the characteristics of highly non-linearity, we are faced to meet the promptness and convenience in field process. In this study, by the Gaussian approximation for the observed data and a priori information, fast Bayesian inversion scheme is developed and applied to the model problem with electric well logging and dipole-dipole resistivity data. Each covariance matrices are induced by geostatistical method and optimization technique resulted in maximum a posteriori information. Especially a priori information is evaluated by the cross-validation technique. And the uncertainty analysis was performed to interpret the resistivity structure by simulation of a posteriori covariance matrix.

• Economic and Environmental Geology
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• v.28 no.4
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• pp.433-438
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• 1995

The most popular minimization method is based on the least-squares criterion, which uses the $L_2$ norm to quantify the misfit between observed and synthetic data. The solution of the least-squares problem is the maximum likelihood point of a probability density containing data with Gaussian uncertainties. The distribution of errors in the geophysical data is, however, seldom Gaussian. Using the $L_2$ norm, large and sparsely distributed errors adversely affect the solution, and the estimated model parameters may even be completely unphysical. On the other hand, the least-absolute-deviation optimization, which is based on the $L_1$ norm, has much more robust statistical properties in the presence of noise. The solution of the $L_1$ problem is the maximum likelihood point of a probability density containing data with longer-tailed errors than the Gaussian distribution. Thus, the $L_1$ norm gives more reliable estimates when a small number of large errors contaminate the data. The effect of outliers is further reduced by M-fitting method with Cauchy error criterion, which can be performed by iteratively reweighted least-squares method.

• Geophysics and Geophysical Exploration
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• v.5 no.1
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• pp.23-32
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• 2002

Capacitively-coupled resistivity (CCR) system is known to be very useful where galvanic contact to earth is impossible, such as the area covered with thick ice, snow, concrete or asphalt. This system injects current non-galvanically, i.e., capacitively to earth through line antenna and measures potential difference in a same manner. We derived geometric factor for two types of antenna configuration and presented the method of processing and converting the data obtained with CCR system suitable to conventional resistivity inversion analysis. The CCR system, however, has limitations on use at conductive area or electrically noisy area since it is very difficult to inject sufficient current to earth with this system as with conventional resistivity system. This causes low SM ratio when acquiring data with CCR system and great care must be taken in acquiring data with this system. Additionally the uniform contact between line antennas and earth is also crucial factor to obtain good S/N ratio data. The CCR method, however, enables one to perform continuous profiling over a survey line by dragging entire system and thus will be useful in rapid investigation of conductivity distribution in shallow subsurface.

• International Union of Geodesy and Geophysics Korean Journal of Geophysical Research
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• v.25 no.1
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• pp.23-34
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• 1997

Seismic tomography using the graph theoretical method of ray tracing is performed in two synthetic data sets with laterally varying velocity structures. The straight-ray tomography shows so poor results in imaging the laterally varying velocity structure that the ray-traced tomographic techniques should be used. Conventional ray tracing methods have serious drawbacks, i.e. problems of convergence and local minima, when they are applied to seismic tomography. The graph theretical method finds good approximated raypaths in rapidly varying media even in shadow zones, where shooting methods meet with convergence problems. The graph theoretical method ensures the globally minimal traveltime raypath while bending methods often cause local minima problems. Especially, the graph theoretical method is efficient in case that many sources and receivers exist, since it can find the traveltimes and corresponding raypaths to all receivers from a specific source at one time. Moreover, the algorithm of graph theoretical method is easily applicable to the ray tracing in anisotropic media, and even to the three dimensional case. Among the row-active inversion techniques, the conjugate gradient (CG) method is used because of fast convergence and high efficiency. The iterative sequence of the ray tracing by the graph theoretical method and the inversion by the CG method is an efficient and robust algorithm for seismic tomography in laterally varying velocity structures.

• International Union of Geodesy and Geophysics Korean Journal of Geophysical Research
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• v.26 no.1
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• pp.1-14
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• 1998

Various numerical methods for the two dimensional shallow water equations have been applied to the problems of flood routing, tidal circulation, storm surges, and atmospheric circulation. These methods are often based on the Alternating Direction Implicity(ADI) method. However, the ADI method results in inaccuracies for large time steps when dealing with a complex geometry or bathymetry. Since this method reduces the performance considerably, a fully implicit method developed by Wilders et al. (1998) is used to improve the accuracy for a large time step. Finite Difference Methods are defined on a rectangular grid. Two drawbacks of this type of grid are that grid refinement is not possibile locally and that the physical boundary is sometimes poorly represented by the numerical model boundary. Because of the second deficiency several purely numerical boundary effects can be involved. A boundary fitted curvilinear coordinate transformation is used to reduce these difficulties. It the curvilinear coordinate transformation is used to reduce these difficulties. If the coordinate transformation is orthogonal then the transformed shallow water equations are similar to the original equations. Therefore, an orthogonal coorinate transformation is used for defining coordinate system. A multigrid (MG) method is widely used to accelerate the convergence in the numerical methods. In this study, a technique using a MG method is proposed to reduce the computing time and to improve the accuracy for the orthogonal to reduce the computing time and to improve the accuracy for the orthogonal grid generation and the solutions of the shallow water equations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1110-1127
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• 2022

To improve the training efficiency and generalization performance of a support vector machine (SVM) in a large-scale set, an optimal SVM learning method based on adaptive sparse sampling and the granularity shift factor is presented. The proposed method combines sampling optimization with learner optimization. First, an adaptive sparse sampling method based on the potential function density clustering is designed to adaptively obtain sparse sampling samples, which can achieve a reduction in the training sample set and effectively approximate the spatial structure distribution of the original sample set. A granularity shift factor method is then constructed to optimize the SVM decision hyperplane, which fully considers the neighborhood information of each granularity region in the sparse sampling set. Experiments on an artificial dataset and three benchmark datasets show that the proposed method can achieve a relatively higher training efficiency, as well as ensure a good generalization performance of the learner. Finally, the effectiveness of the proposed method is verified.

• Geophysics and Geophysical Exploration
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• v.14 no.2
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• pp.152-157
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• 2011

The small-loop electromagnetic (EM) method is one of the rapid and non-destructive geophysical methods and has been used widely for many geophysical investigations, particularly for shallow engineering and environmental surveys. Especially in the shallow marine environment, the small-loop EM technique is very effective because of rapid and convenient data acquisition, large signal and low noise level. However, the method has been rarely applied in the very conductive marine environment since it's penetration or investigation depth might be considered too low. In this study, we demonstrated that the small-loop EM method can be effectively applied in the extremely conductive marine environment through the analysis of 1D small-loop EM data. Furthermore, we confirmed that the resistivity distribution under the sea bottom can be quantitatively predicted from the 1D inversion results of synthetic and field data.

• Proceedings of the Korean Geotechical Society Conference
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• 1999.10a
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• pp.309-312
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• 1999

In recent years there has been a steady increase in geoenvironmental engineering projects where geotechnical engineering has been combined with environmental concerns. Many of these projects involve some investigation on contaminant and leachate flume in the ground and landfill. In this study, investigation on leachate around the waste landfill was carried out to detect the leaked and contaminated area. Many techniques such as geophysical, drilling and sampling method were applied. As a result of this study, the concentration of leachate and the point of leachate leaking around landfill were found out, and countermeasures for cut-off of leachate flow from landfill were investigated.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.10a
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• pp.434-478
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• 2006

Stress waves have been used for geophysical and geotechnical applications for more than 50 years. The early-stage applications were simply based on travel-time measurements of stress waves and limited to site characterization. Currently stress-wave techniques are expanded to monitoring processes for grouting of damaged geotechnical structures, compaction of embankment, and deformational analyses for static geotechnical problems. Seismic techniques used to be good enough for rough estimators of engineering properties. Nowadays, the sophisticated modeling theory of stress-wave propagation substantially improved reliability and accuracy of the seismic techniques. In this paper, difficulties involved in currently available seismic techniques are discussed and analyzed. Herein some recently-developed non-intrusive seismic techniques, which make optimal use of stress waves for further improvement of reliability and accuracy, are also presented.

• 한국지구물리탐사학회:학술대회논문집
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• 2009.05a
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• pp.73-87
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• 2009

Geophysical survey for unconformity-type uranium deposit applied to this study area in Athabaska Basin, Canada were carried out airborne TEM and magnetic, resistivity-induced polarization (DC-IP), puser seismic reflection and well-logging method. The results of airborne survey interpreted the lithological boundary, geological structures, and conductors. Also, these results decided to main targets for ground DC-IP survey. The Low resistivity and the high chargeability slices of 3D modeling interpreted from DC-IP survey response for conductors related to hydrothermal alteration zones and fault-controlled graphitic zones occurring at the unconformity-type uranium deposit, and they confirmed by diamond drilling. Seismic results interpreted to lake bottom surface, alluvium layer and intra-sandstone faults. We suggest the resonable field data acquisition of DC-IP method on the land or the lake in Athabaska Basin.