• The Journal of Engineering Geology
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• v.27 no.3
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• pp.305-312
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• 2017

The most effective way to distinguish subsurface interfaces that produce various geophysical responses is through the integration of multiple geophysical methods, with each method detecting both a complementary and unique set of distinct physical properties relating to the subsurface. In this study, shallow seismic reflection (SSR) and ground penetrating radar (GPR) surveys were conducted at the Cheongju-Gadeok site of the Korea National Groundwater Monitoring Network to map the water table, which was measured at 12 m depth during the geophysical surveys. The water table proved to be a good target reflector in both datasets, as the abrupt transition from the overlying unsaturated weathered rock to the underlying saturated weathered rock yielded large acoustic impedance and dielectric constant contrasts. The two datasets were depth converted and integrated into a single section, with the SSR and GPR surveys conducted to ensure subsurface imaging at approximately the same wavelength. The GPR data provided detailed information on the upper ~15 m of the section, whereas the SSR data imaged structures at depths of 10-45 m. The integrated section thus captured the full depth coverage of the sandy clay, water table, weathered rock, soft rock, and hard rock structures, which correlated well with local drillcore and water table observations. Incorporation of these two geophysical datasets yielded a synthetic section that resembled a simplified aquifer model, with the best-fitting seismic velocity, dielectric constant, and porosity of the saturated weathered layer being $v_{seismic}=1000m/s$, ${\varepsilon}_r=16$, and ${\phi}=0.32$, respectively.

• Geophysics and Geophysical Exploration
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• v.15 no.4
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• pp.177-189
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• 2012

Evaluation of three-dimensional ore body modeling has been performed by applying the geostatistical integration technique to multiple geophysical (electrical resistivity, MT) and geological (borehole data, physical properties of core) information. It was available to analyze the resistivity range in borehole and other area through multiple geophysical data. A correlation between resistivity and density from physical properties test of core was also analyzed. In the case study results, the resistivity value of ore body is decreased contrast to increase of the density, which seems to be related to a reason that the ore body (magnetite) includes heavy conductive component (Fe) in itself. Based on the lab test of physical properties in iron mine region, various geophysical, geological and borehole data were used to provide ore body modeling, that is electrical resistivity, MT, physical properties data, borehole data and grade data obtained from borehole data. Of the various geostatistical techniques for the integrated data analysis, in this study, the SGS (sequential Gaussian simulation) method was applied to describe the varying non-homogeneity depending on region through the realization that maintains the mean and variance. With the geostatistical simulation results of geophysical, geological and grade data, the location of residual ore body and ore body which is previously reported was confirmed. In addition, another highly probable region of iron ore bodies was estimated deeper depth in study area through integrated modeling.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.237-240
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• 2004

In this study, the digital image processing with image enhancement based on homomorphic filtering was performed using geophysical imaging data such as gravity, magnetic data and sub-scenes of satellite images such as LANDSAT, IKONOS, and KOMPSAT. Windows application program for executing homomorphic filtering was designed and newly implemented. In general, homomorphic filtering is technique that is based on Fourier transform, which enhances the contrast of image by removing the low frequencies and amplifying the high frequencies in frequency domain. We can enhance the image selectively using homomorphic filtering as compared with the existing method, which enhance the image totally. Through several experiment using remotely sensed imagery and geophysical image with this program, it is concluded that homomorphic filtering is more effective to reveal distinct characteristics for some complicated and multi-associated features on image data.

• Journal of Korean Tunnelling and Underground Space Association
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• v.6 no.2
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• pp.101-111
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• 2004

In order to guarantee the stability of a tunnel and its optimum design, it is very important to obtain enough ground investigation data. In realty, however, it is not the case due to the limitation of measuring spatially distributed data and economical reasons. Especially, there are regions where drilling is impossible due to civil appeal and mountainous topology, and it is also difficult to estimate rock mass classes quantitatively with only geophysical exploration data. In this study, therefore, 3 dimensional multiple indicator kriging (3D-MI kriging), which can incorporate geophysical exploration data and drill core data off a tunnel center line, is proposed to cope with such problems. To this end, two dimensional mutiple indicator kriging, which is one of the geostatistical techniques, is extended for three dimensional analysis. Also, the proposed 3D-MI kriging was applied to determine the rock mass classes by RMR system for the design of a Kyungbu express rail way tunnel.

• Journal of the Korean Geotechnical Society
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• v.19 no.5
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• pp.319-326
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• 2003

In site investigation for tunnel designs, nowadays, geophysical exploration such as seismic exploration and electric resistivity exploration as well as drilling logging is frequently carried out. A method which can systematically make the utmost use of all available data obtained from investigation, therefore, is strongly required for the optimal evaluation of ground conditions in terms of rock mass class, etc. Many researchers have proposed using qualitative data to cope with the lack of quantitative data. In this study, an evaluation technique of rock mass classes in undrilled region was proposed based upon multiple indicator kriging method which is a geostatistical technique. It was shown that two types of data with different degree of uncertainty, for example, drilling logging data and geophysical exploration data, could be simultaneously utilized in evaluating rock mass classes for a real tunnel design.

• Proceedings of the KSRS Conference
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• v.1
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• pp.150-152
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• 2006

The DISCOVER Project (${\underline{D}}istributed$ ${\underline{I}}nformation$ ${\underline{S}}ervices$ for ${\underline{C}}limate$ and ${\underline{O}}cean$ products and ${\underline{V}}isualizations$ for ${\underline{E}}arth$ ${\underline{R}}esearch$) is a NASA funded Earth Science REASoN project that strives to provide highly accurate, carefully calibrated, long-term climate data records and near-real-time ocean products suitable for the most demanding Earth research applications via easy-to-use display and data access tools. A key element of DISCOVER is the merging of data from the multiple sensors on multiple platforms into geophysical data sets consistent in both time and space. The project is a follow-on to the SSM/I Pathfinder and Passive Microwave ESIP projects which pioneered the simultaneous retrieval of sea surface temperature, surface wind speed, columnar water vapor, cloud liquid water content, and rain rate from SSM/I and TMI observations. The ocean products available through DISCOVER are derived from multi-sensor observations combined into daily products and a consistent multi-decadal climate time series. The DISCOVER team has a strong track record in identifying and removing unexpected sources of systematic error in radiometric measurements, including misspecification of SSM/I pointing geometry, the slightly emissive TMI antenna, and problems with the hot calibration source on AMSR-E. This in-depth experience with inter-calibration is absolutely essential for achieving our objective of merging multi-sensor observations into consistent data sets. Extreme care in satellite inter-calibration and commonality of geophysical algorithms is applied to all sensors. This presentation will introduce the DISCOVER products currently available from the web site, http://www.discover-earth.org and provide examples of the scientific application of both the diurnally corrected optimally interpolated global sea surface temperature product and the 4x-daily global microwave water vapor product.

• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.314-321
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• 2007

Recently, multi-dimensional joint inversion of geophysical data based on fundamentally different physical properties is being actively studied. Joint inversion can provide a way to obtaining much more accurate image of the subsurface structure. Through the joint inversion, furthermore, it is possible to directly estimate non-geophysical material properties from geophysical measurements. In this study, we developed a new algorithm for jointly inverting dc resistivity and seismic traveltime data based on the multiple constraints: (1) structural similarity based on cross-gradient, (2) correlation between two different material properties, and (3) a priori information on the material property distribution. Through the numerical experiments of surface dc resistivity and seismic refraction surveys, the performance of the proposed algorithm was demonstrated and the effects of different regularizations were analyzed. In particular, we showed that the hidden layer problem in the seismic refraction method due to an inter-bedded low velocity layer can be solved by the joint inversion when appropriate constraints are applied.

• Journal of the Korean earth science society
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• v.23 no.1
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• pp.15-29
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• 2002

Bayesian inversion for gravity and resistivity data was performed to investigate the cavity structure appearing as a lava tunnel in Cheju Island, Korea. Dipole-dipole DC resistivity data were proposed for a prior information of gravity data and we applied the geostatistical techniques such as kriging and simulation algorithms to provide a prior model information and covariance matrix in data domain. The inverted resistivity section gave the indicator variogram modeling for each threshold and it provided spatial uncertainty to give a prior PDF by sequential indicator simulations. We also presented a more objective way to make data covariance matrix that reflects the state of the achieved field data by geostatistical technique, cross-validation. Then Gaussian approximation was adopted for the inference of characteristics of the marginal distributions of model parameters and Broyden update for simple calculation of sensitivity matrix and SVD was applied. Generally cavity investigation by geophysical exploration is difficult and success is hard to be achieved. However, this exotic multiple interpretations showed remarkable improvement and stability for interpretation when compared to data-fit alone results, and suggested the possibility of diverse application for Bayesian inversion in geophysical inverse problem.

• Geophysics and Geophysical Exploration
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• v.6 no.4
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• pp.187-194
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• 2003

A small-loop electromagnetic (EM) system using multiple frequencies has advantages in survey speed and cost despite of limitation on its depth of investigation. Therefore, small-loop EM surveys have been frequently used on various site investigations involving engineering and environmental problems. We have developed a subsurface imaging technique using small loop EM data. We used a one-dimensional (ID) inversion method to reconstruct a subsurface image from frequency EM sounding data. Tests using simulated data show that the method can reasonably recover the subsurface resistivity structure. Also, the method was tested on field data obtained with multiple frequency small loop EM system at a farm in Chunchon, Korea. The resistivity image obtained form field data compares favorably with the image from the dipole-dipole resistivity survey.

• Geophysics and Geophysical Exploration
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• v.6 no.4
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• pp.180-186
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• 2003

We have developed an one-dimensional (ID) inversion program that can invert multiple frequency small-loop EM data from horizontal coplanar (HCP) and vertical coplanar (VCP) configurations. The inverse problem is solved using least-squares method with active constraint balancing (ACB) method and Jacobian matrix is calculated analytically. Tests using synthetic data from simple ID models indicate that conductivity and depth of each layer can be estimated properly when both real and imaginary data are used together.