• Atmosphere
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• v.31 no.2
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• pp.185-198
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• 2021

In this study, we examined a spatial downscaling method based on Gradient and Inverse Distance Squared (GIDS) weighting to produce high-resolution grid data from a numerical weather prediction model over Korean Peninsula with complex terrain. The GIDS is a simple and effective geostatistical downscaling method using horizontal distance gradients and an elevation. The predicted meteorological variables (e.g., temperature and 3-hr accumulated rainfall amount) from the Limited-area ENsemble prediction System (LENS; horizontal grid spacing of 3 km) are used for the GIDS to produce a higher horizontal resolution (1.5 km) data set. The obtained results were compared to those from the bilinear interpolation. The GIDS effectively produced high-resolution gridded data for temperature with the continuous spatial distribution and high dependence on topography. The results showed a better agreement with the observation by increasing a searching radius from 10 to 30 km. However, the GIDS showed relatively lower performance for the precipitation variable. Although the GIDS has a significant efficiency in producing a higher resolution gridded temperature data, it requires further study to be applied for rainfall events.

• Journal of the Korean Geotechnical Society
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• v.22 no.2
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• pp.55-68
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• 2006

For the reliable prediction of spatial geotechnical data, a procedure to build the Geotechnical Information System (GTIS) based on geo-knowledge within the frame of GIS technology was developed by introducing a couple of new concepts of the extended area containing the study area and the additional site visit for acquiring surface geological data. To build the GTIS for Gyeongju as the case study of regional model application, intensive site investigations and pre-existing geotechnical data collections were performed and additional site visit was also carried out for acquiring surface geo-layer data in accordance with the developed procedure. Within the GTIS based on geo-knowledge for Gyeongiu area, the spatially distributed geo-layers across the extended area were predicted using the geostatistical kriging method and those for the study area were extracted. Furthermore, the spatial distribution maps for the thickess of geo-layers and the depth to bedrock were constructed for the practical use in geotechnical field. It was evaluated that the GTIS based on geo-knowledge developed in this study is superior to the conventional geotechnical GIS in terms of both the standard deviation and the geological expert judgment.

• Economic and Environmental Geology
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• v.46 no.4
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• pp.313-327
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• 2013

In the study, three-dimensional geostatistical simulations on McMurray Formation which is the largest oil sand reservoir in Athabasca area, Canada were performed, and the optimal site for steam assisted gravity drainage (SAGD) was selected based on the predictions. In the selection, the factors related to the vertical extendibility of steam chamber were considered as the criteria for an optimal site. For the predictions, 110 borehole data acquired from the study area were analyzed in the Markovian transition probability (TP) framework and three-dimensional distributions of the composing media were predicted stochastically through an existing TP based geostatistical model. The potential of a specific medium at a position within the prediction domain was estimated from the ensemble probability based on the multiple realizations. From the ensemble map, the cumulative thickness of the permeable media (i.e. Breccia and Sand) was analyzed and the locations with the highest potential for SAGD applications were delineated. As a supportive criterion for an optimal SAGD site, mean vertical extension of a unit permeable media was also delineated through transition rate based computations. The mean vertical extension of a permeable media show rough agreement with the cumulative thickness in their general distribution. However, the distributions show distinctive disagreement at a few locations where the cumulative thickness was higher due to highly alternating juxtaposition of the permeable and the less permeable media. This observation implies that the cumulative thickness alone may not be a sufficient criterion for an optimal SAGD site and the mean vertical extension of the permeable media needs to be jointly considered for the sound selections.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.05a
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• pp.15-20
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• 2005

기존의 GIS와 지구통계기법을 결합한 연구들은 GIS 데이터베이스로 구축될 자료를 생성하기 위해 2차원 접근방식을 이용해왔다. 그러나 실제 현장 샘플 자료들은 대부분 3차원 공간에 분포하기 때문에 2차원 지구통계기법을 적용하는 것은 실제 자료가 가지고 있는 3차원 위치정보를 정확히 반영할 수 없는 한계가 있다. 본 연구에서는 GIS 기반 자료에 3차원 지구통계기법을 적용하여 공간변수를 예측하고, 생성된 공간변수를 다시 GIS로 반환하여 데이터베이스로 구축하는 결합 모델을 개발하였다. 3차원 지구통계기법을 결합한 결과 보다 정확한 공간변수 예측을 확인할 수 있었고, 그 결과를 GIS에서 다시 활용할 수 있었다.

• 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

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.609-619
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• 2010

Geostatistical data among spatial data is analyzed in three stages: (1) variogram estimation, (2) model fitting for the estimated variograms and (3) spatial prediction using the fitted variogram model. It is very important to estimate the variograms properly as the first stage(i.e., variogram estimation) affects the next two stages. In general, the variogram is estimated with the moment estimator. To estimate the variogram, we have to decide the 'lag increment' or the 'number of lags'. However, there is no established rule for selecting the number of lags in estimating the variogram. The present paper proposes a method of choosing the optimal number of lags based on the PRESS statistic. To show the usefulness of the proposed method, we perform a small simulation study and show an empirical example with with air pollution data from Korea.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.288-295
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• 2003

The relationship between the reflection number obtained from seismic reflective survey and the rock strength value obtained from TBM excavation is examined, and the procedure of the conversion from the reflection number to the rock strength value is proposed. Subsequently, geostatistical method is employed to evaluate the rock properties ahead of the tunnel face and around the tunnel with good precision, using both the seismic reflective survey data and the TBM driving data for the purpose of the tunnel driving and enlargement. The applicability of this evaluation method is examined at the actual tunnel site.

• 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.

• 한국지구물리탐사학회:학술대회논문집
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• 2009.05a
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• pp.101-118
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• 2009

In order to invest in overseas mineral projects, it is necessary to have a ability of technical and financial evaluation. Reserve estimation is the most important for mineral appraisal. Geostatistical evaluation of tonnage and grade promises more accurate reserve estimation than traditional methods such as polygon, inverse distance method and so on even if it has some uncertainty. Selection of a mining method and a mineral processing is also important because capex and opcosts of a mineral project is due to the selection. Mineral project is usually evaluated financially using NPV and IRR which are calculated through DCF(Discount Cash Flow). Uncertainty of a mineral project is analyzed statistically using sensitivity analysis and montecarlo simulation.