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31.
Environmental studies require multivariate data such as chemical concentrations with space-time coordinates. There are two
general conditions related to such data: the existence of correlations among the coregionalized variables and the differences
in numbers of data which occur because of insufficient data caused by measurement error or bad weather conditions. This study
proposes geostatistical techniques for space-time multivariate modeling that take into consideration these correlations and
data absences. These techniques consist of suitable modeling of semivariograms and cross-semivariograms for quantifying correlation
structures among multivariables and of extending standardized ordinary cokriging. The tensor product cubic smoothing surface
method is used for space-time semivariogram modeling. These methods are applied to the chemical component data of the Ariake
Sea, a typical closed sea in southwest Japan. In order to clarify environmental changes in the Ariake Sea, the concentration
data of four nutritive salts (NO2–N, NO3–N, NH4–N, and PO4–P) at 38 stations over 25 years are used as environmental indicators. For each of the kinds of data, there are spaces and
times for which there is no data available. The effectiveness of the modeling of space-time semivariograms and the high estimation
capability of the extended cokriging are demonstrated by cross-validation. Compared with ordinary kriging for a single variable,
multivariate space-time standardized ordinary cokriging can provide a more detailed concentration map of nutritive salts and
while elucidating their temporal changes over sparsely spaced data areas. In the space-time models by ordinary kriging, on
the other hand, smooth trends are obvious. 相似文献
32.
Katsuaki Koike Toshiaki Minta Shinya Ishizaka Michito Ohmi 《Natural Resources Research》1996,5(1):23-32
An application of a geotechnical database system for primary evaluation of ground-water resources in a sedimentary basin is proposed. The database consists of 1200 borehole logs including geologic columns,in situ test results, ground-water level, water quality data, and resistivity logs. The Kumamoto plain, situated in southwest Japan, is chosen as a study area. The evaluation process consists of two steps: (1) modeling of shapes of water-bearing strata, and (2) modeling of distribution of physical quantity which has some relationship with the porosity of those strata. In step (1), the shapes of upper and/or lower surface of the pyroclastic flow deposits and the andesitic lava were determined, whereas the three-dimensional distribution model of resistivity was constructed from resistivity logging data obtained from 100 boreholes and using the proposed interpolation method in the step (2). An empirical equation between the porosity and the resistivity of the lava was also identified. The integration of two types of model and the empirical equation contributed to an estimate of the total volume of the ground-water under the study area. 相似文献
33.
Magnetotelluric resistivity modeling for 3D characterization of geothermal reservoirs in the Western side of Mt. Aso, SW Japan 总被引：1，自引：1，他引：1
Hisafumi Asaue Katsuaki Koike Toru Yoshinaga Shinichi Takakura 《Journal of Applied Geophysics》2006,58(4):296
Geothermal reservoirs are usually located at a depth range of 2 to 5 km, so to efficiently utilize such resources an advanced prospecting method is needed to detect these deep geologic structures. This study aimed to three-dimensionally characterize geothermal reservoirs by a combination of Magnetotelluric (MT) survey, inversion analysis of apparent resistivity, and interpolation of the resistivity data obtained. The western side of Mt. Aso crater, southwest Japan, was chosen as the case study area. Three hot springs exist there and a fault is assumed to go in the direction connecting them. A MT survey was carried out at 26 sites and the data processed by a remote reference method to reduce artificial noises. Based on skewness and Mohr circle analyses of the impedance tensor, the local geologic structure at each site could be approximated as horizontally layered and therefore, a one-dimensional inversion analysis was applied to the MT raw data. The resultant resistivity column data were then interpolated by the three-dimensional optimization principle method. The resistivity distributions obtained clarified continuous conductors with especially low resistivity (less than 10 Ω·m) at the hot springs along the fault. Because the resistivity decreases largely with an abundance of clay minerals, the conductors could be considered to correspond with the cap rocks. Thus, two geothermal reservoirs, whose shapes were estimated to be pillar, were detected under the cap rocks in an elevation range of − 1000 to − 3000 m. By comparing the resistivity distributions with the temperature distributions based on fluid-flow calculations at a steady state using FEM, the validity of the location and dimension of the estimated reservoirs were confirmed. 相似文献
34.
Three-dimensional distribution analysis of phosphorus content of limestone through a combination of geostatistics and artificial neural network 总被引：1，自引：0，他引：1
One of the factors that determines the suitability of limestone for industrial use and its commercial value is phosphorus
(P) content, i.e., the weight percentage of phosphorus contained in small quantities of limestone. Because P content changes
locally, geostatistical techniques including semivariogram, ordinary kriging, and conditional indicator sequential simulation
were used in this study to identify the spatial correlation of P content and to estimate its three-dimensional distribution
in an open-pit mine. The P content data at 43,000 points of five different bench levels were analyzed. It was found that the
horizontal semivariograms produced by using the data at the same bench level show anisotropic behavior and are represented
by the sum of two spherical models with different ranges and sills. The twelve vertical semivariograms were also constructed
from P content in boring cores. After these semivariograms were classified into four types, a multilayered neural network
was applied to clarify the horizontal distribution of each one. One of the twelve semivariograms was assigned to an arbitrary
grid point in the study area by the criterion that its type is the same as the one estimated at the point and the borehole
site producing the semivariogram is the nearest to the point. With this technique, ordinary kriging combined with the semivariogram
of borehole data provided a proper estimation of P content in the depth direction. 相似文献