• Economic and Environmental Geology
• /
• v.29 no.5
• /
• pp.575-587
• /
• 1996

The purpose of this study is to develop geostatistical methods for selection of prospective areas of polymetallic nodule deposits in KODOS (Korea Deep Ocean Study) area of the North-East Pacific Ocean. In this study $110{\times}165$ grid system was used, and each node represents the center of an estimated block of $1km{\times}1km$. The ordinary kriging was applied to SeaBeam2000 data in order to evaluate the bathymetry. A structural analysis (variogram) of the bathymetry data was carried out for constructing digital terrain model (DTM) and the maximum slopes of the bathymetry were calculated by DTM data. The above method can be used to solve the problem that is resulted from the lack of theory of a change of support model for the maximum slope of the bathymetry. The ordinary kriging and the indicator kriging were used to evaluate the nodule abundance, and the different two kriging methods were compared to evaluate the accuracy for the estimation of the nodule abundance. It has been shown that indicator kriging was better estimation tool than the ordinary kriging. The overlay map is presented for the selection of potentially minable sites by combining the two indicator maps of the nodule abundance and the maximum slope of bathymetry. This overlay map could be utilized to establish follow-up survey and to investigate the potentially minable sites in the KODOS area.

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

• Economic and Environmental Geology
• /
• v.26 no.2
• /
• pp.207-215
• /
• 1993

In modem petroleum reservoir engineering, the characterization of reservoir heterogeneities is very important to accurately understand and predict reservoir production performance. Formation evaluation for the description of reservoir is generally conducted by performing the analysis of well logging, core testing, and well testing. However, the measured data points by well logging or core testing are in general very sparse and hence reservoir properties should be interpolated and extrapolated from measured points to uncharacterized areas. In assigning the data for the unknown points, simple averaging technique is not feasible as optimum estimation method since this method does not account the spatial relationship between the data points. The main goal of this work is to develop PC-version of multi-purpose geostatistical model in which several stages are systematically proceeded. In the development of model, the simulator employs a automatic selection of semivariogram function such as exponential or spherical model with the best values of $R^2$. The simulator also implements a special algorithm for the fitting of semivariogram function to experimental sernivariogram. The special algorithm such as trial and error scheme is devised since this method is much more reliable and stable than Gauss-Newton method. The simulator has been tested under stringent conditions and found to be stable. Finally, the validity and the applicability of the developed model have been studied against some existing actual field data.

• Journal of the Korean earth science society
• /
• v.35 no.2
• /
• pp.115-130
• /
• 2014

The growing possibility of the disaster due to severe weather calls for disaster prevention and water management measures in South Korea. In order to prevent a localized heavy rain from occurring, the rainfall must be observed and predicted quantitatively. In this study, we developed an adjustment algorithm to estimate the radar precipitation applying to the local gauge correction (LGC) method which uses geostatistical effective radius of errors of the radar precipitation. The effective radius was determined from the errors of radar rainfall using geostatistical method, and we adjusted radar precipitation for four heavy rainfall events based on the LGC method. Errors were decreased by about 40% and 60% in adjusted hourly rainfall accumulation and adjusted total rainfall accumulation for four heavy rainfall events, respectively. To estimate radar precipitation for localized heavy rain events in summer, therefore, we believe that it was appropriate for this study to use an adjustment algorithm, developed herein.

• Journal of the Korean Society of Groundwater Environment
• /
• v.7 no.3
• /
• pp.125-132
• /
• 2000

pH, EC and TDS are basic components in the investigation of groundwater quality, and are very important to the preliminary assessment of groundwater quality. These three chemical components investigated at the Youngsan and Sumjin river basins in 1998 suggest that the groundwater quality is generally good in these basins. Linear regression analysis shows that TDS versus EC has an linear correlation, but EC versus pH, and TDS versus pH have nearly no correlation. The relation of TDS and EC is 1.0 mg/1=1.52 $mu\textrm{S}$/cm, and it is the quality of natural water. In geostatistical analysis. three kinds of data are stationary random functions and they have exponential variograms. According to the isopleth maps of the groundwater quality, the groundwater quality of the Youngsan river basin is more contaminated than that of the Sumjin river basin. The isopleth maps of TDS and EC show very similar patterns because of the strong correlation between TDS and EC. The minimum and maximum values of the groundwater quality data are not reflected on the isopleth maps because kriging produces smooth distributions with minimum estimation variances.

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

• Journal of Korea Water Resources Association
• /
• v.36 no.2
• /
• pp.143-152
• /
• 2003

This paper suggests the improvement of the Sumjinkang for the estimation of areal averages of heavy rainfall events based on the optimal network and three existing networks. The problem consists of minimizing an objective function which includes both the accuracy of the areal mean estimation as expressed by the Kriging variance and the economic cost of the data collection. The wellknown geostatistical variance-reduction method is used in combination with SATS which is an algorithm of minimization. At the first stage, two kinds of optimal solutions are obtained by two trade-off coefficients. One of them is a optimal solution, the other is an alternative. At the second stage, a quasi optimal network and a quasi alternative are suggested so that the existing raingages near to the selected optimal raingages are included in the two solutions instead of gages of new gages.

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

• Journal of Korea Water Resources Association
• /
• v.43 no.11
• /
• pp.933-944
• /
• 2010

This study compares the CEM and SGS methods which are geostatistical stochastic simulation methods for assessing the uncertainty by spatial variability in the estimation of the spatial distribution of probability rainfall. In the stochastic simulations using CEM and SGS, two methods show almost similar results for the reproduction of spatial correlation structure, the statistics (standard deviation, coefficient of variation, interquartile range, and range) of realizations as uncertainty measures, and the uncertainty distribution of basin mean rainfall. However, the CEM is superior to SGS in aspect of simulation efficiency.

• Journal of Soil and Groundwater Environment
• /
• v.10 no.5
• /
• pp.52-60
• /
• 2005

The conceptual model of under-sampled study area will include a great amount of uncertainty. In this study, we investigate the applicability of Markov chain model in a spatial domain as a tool for minimizing the uncertainty arose from the lack of data. A new formulation is developed to generalize the previous two-dimensional coupled Markov chain model, which has more versatility to fit any computational sequence. Furthermore, the computational algorithm is improved to utilize more conditioning information and reduce the artifacts, such as the artificial parcel inclination, caused by sequential computation. A generalized 20 coupled Markov chain (GCMC) is tested through applying a hypothetical soil map to evaluate the appropriateness as a substituting model for conventional geostatistical models. Comparing to sequential indicator model (SIS), the simulation results from GCMC shows lower entropy at the boundaries of indicators which is closer to real soil maps. For under-sampled indicators, however, GCMC under-estimates the presence of the indicators, which is a common aspect of all other geostatistical models. To improve this under-estimation, further study on data fusion (or assimilation) inclusion in the GCMC is required.