| Project/Area Number |
10555351
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 展開研究 |
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| Research Field |
資源開発工学
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| Research Institution | Kumamoto University |
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Principal Investigator |
OHMI Michito Kumamoto University, Fac. of Engineering, Professor, 工学部, 教授 (30040405)
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| Co-Investigator(Kenkyū-buntansha) |
HAYASHI Yasuhiro Kumamoto University, Fac. of Engineering, Research Associate, 工学部, 助手 (50274692)
KITAZONO Yoshito Kumamoto University, Fac. of Engineering, AssociateProfessor, 工学部, 助教授 (40094007)
KOIKE Katsuaki Kumamoto University, Fac. of Engineering, Associate Professor, 工学部, 助教授 (80205294)
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| Project Period (FY) |
1998 – 1999
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| Project Status |
Completed (Fiscal Year 1999)
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| Budget Amount *help |
¥12,600,000 (Direct Cost: ¥12,600,000)
Fiscal Year 1999: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 1998: ¥11,600,000 (Direct Cost: ¥11,600,000)
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| Keywords | Geothermal Resources / Magneto-Telluric Method / Resistivity / Temperature / Fault / Hydrothermal Fluid / Electric Exploration / Radon / 地熱調査 / 熱水変質 / MT / インバージョン / 地熱 / 活火山 |
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| Research Abstract |
We examined an exploration system for estimating a three-dimensional temperature distribution in geothermal field through resistivity distribution in the shallow and deep depths. The resistivity data were obtained by electrical exploration and Magneto-Telluric (MT) method. Mt. Aso, which is a typical active volcano and situated in central Kyushu, was chosen as the study site. The main results are summarized as follows.
(1) Fault shape concerning width, dip direction, and dip angle can be estimated from spatial distribution of radon concentrations through combination of a numerical simulation for the movement of radon and the calculation method of number of radon atoms. The radon concentrations on a fault, which has a role of conduit for hydrothermal fluids, show large temporal changes attributable to the activity of volcanic earthquakes.
(2) We have constructed the estimation and interpretation methods of fracture orientation through a combination of satellite-image derived lineaments, d
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igital elevation model data, and digital geologic map. These methods can be used to infer distribution pattern of fractures that have effect on flow path of hydrothermal fluids.
(3) A new method using neural network and geostatistics was applied to estimate distribution of subsurface temperatures from geothermal investigation loggings. In spite of the restricted quantity of sample data, the interpolation results revealed high temperature zones and convection patterns of hydrothermal fluids.
(4) Electrical exploration clarified that the resistivity near the ground surface tends to decrease upon a fault which moved recently. The resistivity distribution in the deep depths of a fault, which is obtained by MT method, is not homogeneous, and the resistivity in largely fractured zones is specially low. Because the resistivity distributions between TE mode and TM mode are quite different, the resistivity of Mt. Aso is thought to have strong anisotropic behavior.
(5) A general relation that the portion with higher temperature has higher resistivity was found through the examination of the resistivity obtained by MT method and the temperature estimated by a finite element method. Furthermore, the resistivity under the discharge zone of hydrothermal fluids was found to be lower than the other areas with the same temperature. Less
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