• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2000.02a
• /
• pp.190-195
• /
• 2000

• Economic and Environmental Geology
• /
• v.35 no.2
• /
• pp.163-170
• /
• 2002

The purpose of this study is to analyze the relationship between geology and geothermal gradient in South Korea using GIS. For the analysis, 352 temperature logging wells were constructed to spatial database and the relationships beween geothermal gradient and geological time and lithology were analyzed using the overlay the wells layer and 1:1,000,000 scale geological map layer. The average of the geothermal aradient of South Korea is 29.34$^{\circ}C$/km. In the geologic sequence, Cenozoic strata has 39.7$0^{\circ}C$/km, Mesozoic strata has 30.63$^{\circ}C$/km , Paleozoic strata has 22.32$^{\circ}C$/km, Proterozoic strata 23.15$^{\circ}C$/km geothermal gradient value. In the lithological aspect, plutonic rocks 33.96$^{\circ}C$/km, sedimentary rocks have 24.78$^{\circ}C$/km and sedimentary and volcanic rocks have 26.85$^{\circ}C$/km geotermal gradient value. The result can be used to develop geothermal energy and hot spring as a reference.

• Proceedings of the Korean Environmental Sciences Society Conference
• /
• 2020.10a
• /
• pp.108-108
• /
• 2020

• Proceedings of the Korean Environmental Sciences Society Conference
• /
• 2019.10a
• /
• pp.175-175
• /
• 2019

• Geophysics and Geophysical Exploration
• /
• v.21 no.2
• /
• pp.125-131
• /
• 2018

2017 Pohang earthquake (M 5.4) was more disastrous than 2016 Gyeongju earthquake (M 5.8), partly because of its shallow focal depth. However, precise focal depth of Pohang earthquake is still controversial. Close crustal model showed 6 ~ 11.5 km in relocation depth, whereas other models showed almost surface range. Geothermal study indicated temperature of $300^{\circ}C$ at depth of 7.5 km. Related with observations of seismogenic layer, the focal depth of Pohang earthquake seems to be 7 km depth as obtained by close model.

• 한국신재생에너지학회:학술대회논문집
• /
• 2009.06a
• /
• pp.608-610
• /
• 2009

지열 분포에 관련된 지질구조의 특성을 파악하기 위하여 지온경사, 지열류량 자료와 인접한 선구조의 방향성에 대한 상관성 분석을 실시하였다. GIS를 이용하여 지열정보데이터베이스에서 발췌한 209개 지온경사 자료와 218개 지열류량 자료에 대하여 전국 광역단열도로부터 가장 인접한 선구조를 추출하고 10도 간격의 방향별 지온경사 및 지열류량 자료 빈도 및 평균값을 그래프에 도시하였다. 인접 선구조의 방향별 지온경사 평균은 $N30^{\circ}{\sim}40^{\circ}W$, $N10^{\circ}{\sim}20^{\circ}E$ 방향에서 $58.9^{\circ}C/km$, $54.9^{\circ}C/km$로 가장 높았고, 인접 선구조의 방향별 지열류량 평균은 $N80^{\circ}{\sim}90^{\circ}W$, $N50^{\circ}{\sim}60^{\circ}W$ 방향에서 98.71 $mW/m^2$, $98.70mW/m^2$로 가장 높았다. 각 선구조 상의 좌표들을 이용하여 지열류량 분포도에서 지열류량 값을 추출한 결과 $N10^{\circ}W{\sim}N40^{\circ}E$, $N60^{\circ}{\sim}70^{\circ}W$, $N50^{\circ}{\sim}60^{\circ}E$ 방향의 지열류량 높은 것으로 나타났다. 결과적으로 지온경사와 지열류량 자료에 대한 인접 선구조의 방향은 북북동, 북서, 서북서 방향이 우세한 것으로 나타났다. 이는 우리나라 조구조 운동과 관련한 단층, 절리 등의 단열구조의 우세 방향과 잘 일치하는 것으로 해석된다.

• The Journal of Engineering Geology
• /
• v.7 no.3
• /
• pp.173-189
• /
• 1997

A study on the geological structure and geothermal gradient distribution was carried out to evaluate the feasibility of developing a new geothermal field in the Yusong area. It is suggested that geothermal water in the Yusong area is closely related with faults, dykes, and their dipping characteristics with the study of geothermal gradient distribution. A fault of EW direction locates in northern boundary of the study area and another fault of N40{\citc}W$ crosses the EW fault at the western part of the study area. Locations of faults are recognized quite well by lineaments, geophysical exploration and geothermal gradient distribution characteristics. Three sets of dyke are found in the study area. According to the result of the geothermal gradient distribution study, the location of geothermal anomaly belt and dykes coincide each other, and the area has the temperature gradient of larger than 3$^{\circ}C$ between the depths of 0.5m and 1.0m below ground surface. The thermal anomaly belt those temperature gradient is larger than 2.5$^{\circ}C$ between the depths of 0.5m and 1.Om below ground surface is expected in the direction of N80{\citc}W$ in the study area. The dirping of dyke is almost vertical according to the linear distribution of dykes on surface and the results of geophysical survey. From the distribution of geothermal anomaly belt and the locations of dyke, three locations for the development of hot spring water could be recommended and the depth that ensure over 4$0^{\circ}C$ geotheraral water is estimated as 170~200m below the ground surface.

• 한국신재생에너지학회:학술대회논문집
• /
• 2008.05a
• /
• pp.646-649
• /
• 2008

최근 유가 폭등으로 관심이 고조되고 있는 청정 재생에너지인 지열자원의 효과적인 개발 및 활용을 위하여 그동안 축적된 지열조사 및 연구정보를 체계적으로 저장,관리, 도시할 수 있는GIS기반의 지열자원 정보시스템을 개발하고자 하였다. 이를 위하여 열물성, 지온경사, 지열류량, 열생산율, 열부존량 등 지열조사 자료를 수집 및 분석하여 공간적 특성과 역할에 따라 기본정보, 참조정보, 분석정보, 부가정보의 4개 자료군, 39개 단위데이터로 분류하였고, 각 단위데이터의 속성 선정과 연계를 위한 GIS 데이터 모델링을 통하여 공간데이터베이스를 설계하였다. 지열자원 정보시스템은 도면표시, 자료조회, 분석/통계등 전반적인 GIS 기능을 이용하여 지열자료의 조회 및 분석이 용이하도록 설계하였다.

• Journal of the Mineralogical Society of Korea
• /
• v.16 no.1
• /
• pp.1-17
• /
• 2003

The chemical composition of the arsenopyrite Ib adjoining“triple mutual contact”arsenopyrite + pyrite + hexagonal pyrrhotite may serve as a useful geothermometer in Stage II. In this study it corresponds to temperature T=33$0^{\circ}C$ and f( $S_2$)=10$^{-9.5}$ atm. And the pyrite-hexagonal pyrrhotite buffer curve indicates the probable range of the two variables; T= 315∼345$^{\circ}C$, and f( $S_2$)=10$^{-1}$0.5/∼10$^{-9}$ atm. The present antimony-bearing arsenopyrite (arsenopyrite Ic) is characterized by relatively high content of antimony, ranging from 4.95 to 8.91 percent Sb by weight and excess of iron and deficiency of anions are evident. Such a high antimonian arsenopyrite has never been known within single grain. But being the high content of antimony as in the arsenopyrite Ic, it does not serve as a geothermometer. The results of microprobe analyses for four pairs of asenopyrite and sphalerite in Stage III indicate the temperature range from 310 to 34$0^{\circ}C$, and sulphur fugacity range from 10$^{-10}$ ∼10$^{-9}$ atm. These values seem to correspond with those inferred from the Fe-As-S system.m..

• Korean Journal of Soil Science and Fertilizer
• /
• v.23 no.2
• /
• pp.87-93
• /
• 1990

A statistical model to predict soil temperature from the ambient meteorological factors including mean, maximum and minimum air temperatures, precipitation, wind speed and snow depth combined with Fourier time series expansion was developed with the data measured at the Suwon Meteorolical Service from 1979 to 1988. The stepwise elimination technique was used for statistical analysis. For the yearly oscillation model for soil temperature with 8 terms of Fourier expansion, the mean square error was decreased with soil depth showing 2.30 for the surface temperature, and 1.34-0.42 for 5 to 500-cm soil temperatures. The $r^2$ ranged from 0.913 to 0.988. The number of lag days of air temperature by remainder analysis was 0 day for the soil surface temperature, -1 day for 5 to 30-cm soil temperature, and -2 days for 50-cm soil temperature. The number of lag days for precipitaion, snow depth and wind speed was -1 day for the 0 to 10-cm soil temperatures, and -2 to -3 days for the 30 to 50-cm soil teperatures. For the statistical soil temperature prediction model combined with the yearly oscillation terms and meteorological factors as remainder terms considering the lag days obtained above, the mean square error was 1.64 for the soil surfac temperature, and ranged 1.34-0.42 for 5 to 500cm soil temperatures. The model test with 1978 data independent to model development resulted in good agreement with $r^2$ ranged 0.976 to 0.996. The magnitudes of coeffcicients implied that the soil depth where daily meteorological variables night affect soil temperature was 30 to 50 cm. In the models, solar radiation was not included as a independent variable ; however, in a seperated analysis on relationship between the difference(${\Delta}Tmxs$) of the maximum soil temperature and the maximum air temperature and solar radiation(Rs ; $J\;m^{-2}$) under a corn canopy showed linear relationship as $${\Delta}Tmxs=0.902+1.924{\times}10^{-3}$$ Rs for leaf area index lower than 2 $${\Delta}Tmxs=0.274+8.881{\times}10^{-4}$$ Rs for leaf area index higher than 2.