• 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.

• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.252-258
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• 2007

We have studied the feasibility of geostatistics approach to enhancing analysis of sparsely obtained seismic data by combining with satellite gravity data. The shallow depth and numerous fishing nets in The Yellow Sea, west of Korea, makes it difficult to do seismic surveys in this area. Therefore, we have attempted to use geostatistics to integrate the seismic data along with gravity data. To evaluate the feasibility of this approach, we have extracted only a few seismic profile data from previous surveys in the Yellow Sea and performed integrated analysis combining with the results from gravity data under the assumption that seismic velocity and density have a high physical correlation. First, we analyzed the correlation between extracted seismic profiles and depths obtained from gravity inversion. Next, we transferred the gravity depth to travel time using non-linear indicator transform and analyze residual values by kriging with varying local means. Finally, the reconstructed time structure map was compared with the original seismic section given in the previous study. Our geostatistical approach demonstrates relatively satisfactory results and especially, in the boundary area where seismic lines are sparse, gives us more in-depth information than previously available.

• Journal of the Korean earth science society
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• v.35 no.1
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• pp.69-87
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• 2014

This paper suggests a conditional simulation framework based on multiple data transformations for geostatistical simulation of compositional data. First, log-ratio transformation is applied to original compositional data in order to apply conventional statistical methodologies. As for the next transformations that follow, minimum/maximum autocorrelation factors (MAF) and indicator transformations are sequentially applied. MAF transformation is applied to generate independent new variables and as a result, an independent simulation of individual variables can be applied. Indicator transformation is also applied to non-parametric conditional cumulative distribution function modeling of variables that do not follow multi-Gaussian random function models. Finally, inverse transformations are applied in the reverse order of those transformations that are applied. A case study with surface sediment compositions in tidal flats is carried out to illustrate the applicability of the presented simulation framework. All simulation results satisfied the constraints of compositional data and reproduced well the statistical characteristics of the sample data. Through surface sediment classification based on multiple simulation results of compositions, the probabilistic evaluation of classification results was possible, an evaluation unavailable in a conventional kriging approach. Therefore, it is expected that the presented simulation framework can be effectively applied to geostatistical simulation of various compositional data.

• Journal of the Korean earth science society
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• v.31 no.7
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• pp.681-690
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• 2010

Inversion result of geophysical data given as a block type was geostatistically simulated with borehole observation given as a point type and was applied to the rock classifying map. The geophysical data generally involved secondary information for the target material and were obtained for overall region. In contrast, borehole data provided direct information for the target material, but tended to be effective only for a narrow range of region and were dealt as a point type. Integrated simulation or kriging interpolation of these two different kinds of information required the covariance for point-point, point-block and block-block. Using the Bssim module included in SGeMS software, integrated result of geophysical data and borehole data were obtained. The results were then compared with the method of geostatistical inversion proposed by authors. Downscaling method used in this study showed relatively more flexible than the geostatistical inversion.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.340-343
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• 2003

This study presents a practical procedure for the Bayesian inversion of geophysical data by Markov chain Monte Carlo (MCMC) sampling and geostatistics. We have applied geostatistical techniques for the acquisition of prior model information, and then the MCMC method was adopted to infer the characteristics of the marginal distributions of model parameters. For the Bayesian inversion of dipole-dipole array resistivity data, we have used the indicator kriging and simulation techniques to generate cumulative density functions from Schlumberger array resistivity data and well logging data, and obtained prior information by cokriging and simulations from covariogram models. The indicator approach makes it possible to incorporate non-parametric information into the probabilistic density function. We have also adopted the MCMC approach, based on Gibbs sampling, to examine the characteristics of a posteriori probability density function and the marginal distribution of each parameter. This approach provides an effective way to treat Bayesian inversion of geophysical data and reduce the non-uniqueness by incorporating various prior information.

• Journal of the Korean earth science society
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• v.32 no.6
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• pp.613-628
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• 2011

Restoration, prediction and noise analysis of geomagnetic data measured in the Korean Peninsula were performed. Restoration methods based on an optimized principal component analysis (PCA) and the geostatistical kriging approach were proposed, and its effectiveness was also interpreted. The PCA-based method seemed to be effective to restore the periodical signals and the geostatistical approach was stable to fill the gaps of measurements. To analyze the noise level for each observatory, the geomagnetic time-series was plotted by scattergram which reflects the spatial variation, using data observed during same period. The scattergram showed that the observation made at Cheongyang seemed to have better quality in spatial continuity and stability, and the restoration result was also better than that of Icheon site. For the restoration, both of the methods, geostatistical and optimizaed PCA, showed stable result when the missing of observation was within 20 points. However, in case of more missing observations than 20 points and prediction problem, the optimized PCA seemed to be closer to the real observation considering the frequency-domain characteristics. The prediction using the optimized PCA seems to be plausible for one day of period for interpretation.

• Journal of the Korean earth science society
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• v.35 no.1
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• pp.29-40
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• 2014

A DC resistivity survey was performed to detect anomalies beneath concrete pavement. A set of high conductive media and planar electrodes were used to lessen the effect's a high contact resistance of concrete. Results of the resistivity survey were analyzed and compared with those of other geophysical surveys such as Ground Penetration Radar (GPR), Impulse Response (IR), and Multi-channel Analysis of Surface Waves (MASW), which were carried out in the same location. The results of resistivity survey showed a high resistive distribution in the section of sink and pavement where a pattern of reinforcement was observed through the GPR survey. Also, a comparison of results between the IR and resistivity surveys indicated that the high resistivity was produced by the high dynamic stiffness in the reinforced section. The co-Kriging of both the results of DC resistivity and MASW surveys at the same location showed that an integrated geostatistical analysis is able to give more accurate description on the anomalous subsurface region than can a separate analysis of each geophysical approach. This study suggests that the integrated geostatistical approaches were used for a decision-making process based on the geophysical surveys.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.943-947
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• 2005

This study was intended to interpose an objection about the analysis of rainfall spatial distribution without a proper standard, and offer the improved approach using 1,he geostatistical analysis method to analyze it. For this, spatially distributed daily rainfall data sets were collected for 41 weather stations in study area, and variogram and correlation analysis were conducted. In the results of correlation analysis, it was found that the longer distance between the stations reduces the correlation of the rainfall data, and maltes the characteristics of the rainfall spatial distribution. The variogram analysis shows that correlation range was less than 50 km for the 17 daily rainfall data sets of total 91 sets. It says that it involves some rike, to determine the application method for rainfall spatial distribution without some qualifications, hence the Application standards of the Rainfall Spatial Distribution Analysis Technique, were essential and that was contingent on characteristics of rainfall and landscape.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2005.10a
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• pp.274-275
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• 2005

• Economic and Environmental Geology
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• v.32 no.1
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• pp.63-72
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• 1999

In order to examine the contamination levels of trace elements in stream sediments in the Chungnam coal mine area, stream sediment and water samples were collected and analyzed for trace elements. The pH of stream water was neutral or weak-alkaline and the mobility of metal in stream sediments was supposed to be low. From the result of cluster analysis, non-polluted sampling stations can be distinguished from polluted sampling stations influenced by mining activities. The trace element concentrations in sediments from non-polluted zone were considered to be the natural backround concentrations of this area. The trace element concentrations in sediment samples from the mining area were higher than those from non-polluted area, and contaminated area of enriched trace element levels need to be properly managed. From the results of discriminant and regression analyses, concentrations of Cd, Cu, Pb AND zN and predicted values of Be, Mo, and Ni in Chungnam coal mine area were found to be lower than those in metal mining areas in Korea.