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Exploration for volcanogenic massive sulfide deposits of the kuroko-type is underway in many places. Clarifying the spatial patterns of the metals in kuroko deposits will be useful for understanding their genetic mechanisms and for future exploration of such types of deposits. This study represents a spatial distribution analysis on the contents of principal metals of kuroko deposits: Cu, Pb, and Zn, in the Hokuroku district, northern Japan, by a feedforward neural network and 1917 sample data at 143 drillhole sites. The network, which consists of three layers, was trained by the principle of SLANS in which the numbers of neurons in the middle layer and training data are changed to improve estimation accuracy. Using the weight coefficients connecting adjacent neurons, sensitivity analysis of the neural network was carried out to identify factors influencing spatial distributions of the three metals. The coordinates depth (z) direction, Bouguer gravity, and specific lithology such as dacite were determined to be influencing factors. The high frequency of the z coordinate signifies that the metal contents differ to a large extent by depth. The sensitivity vector was defined using sensitivity coefficients for x, y, and z coordinates of an estimation point. We determined that the directions of large vectors were different inside and outside of the Hanawa-Ohdate area. This characteristic is considered to originate from the differences in the permeability of fractures that became the paths for rising ore solutions, and the depths that the solutions mixed with sea water. 相似文献
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Luís André Magaia Tada-nori Goto Alaa Ahmed Masoud Katsuaki Koike 《Natural Resources Research》2018,27(3):275-298
Exploring for groundwater in crystalline rocks in semiarid areas is a challenge because of their complex hydrogeology and low potential yields. An integrated approach was applied in central western Mozambique, in an area covered by Precambrian crystalline basement rocks. The approach combined a digital elevation model (DEM), remote sensing, and a ground-based geophysical survey. The aim was to identify groundwater zones with high potential and to identify geological structures controlling that potential. Lineaments were extracted from the DEM that had been enhanced using an adaptive-tilt, multi-directional, shading technique and a non-filtering technique to characterize the regional fracture system. The shallowness and amount of stored groundwater in the fracture zones was assessed using vegetation indices derived from Landsat 8 OLI images. Then, 14 transient electromagnetic (TEM) survey profiles were taken in different geological settings across continuous lineaments that were considered to be aligned along inferred faults. In the central lineament zones, the TEM soundings gave resistivity values of less than 300 Ωm at a depth of 20–80 m. The values varied with location. Conversely, values greater than 400 Ωm were observed at the sites away from the central zones. This contrast is probably caused by the differences in permeability and degree of weathering along the fractured zones. These differences could be key factors in determining groundwater occurrence. By integrating five water-related factors (lineament density, slope, geology, vegetation index, and proximity to lineaments), high groundwater potential zones were located in the vicinity of the lineaments. In these zones, vegetation remains active regardless of the season. 相似文献
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Asep Saepuloh Katsuaki Koike Makoto Omura Masato Iguchi Ari Setiawan 《Bulletin of Volcanology》2010,72(2):221-232
Mt. Merapi, Indonesia, is one of the most active and dangerous volcanoes in the Torrid Zone. This volcano has erupted frequently and has produced pyroclastic flows following the collapse of the summit lava dome. We used Synthetic Aperture Radar (SAR) data acquired by JERS-1 and RADARSAT-1 satellites from April 1996 to July 2006 to clarify the distribution patterns of the pyroclastic flow deposits. The extent of the deposits, termed P-zones, was accurately extracted by ratio operation and low-level feature extraction from SAR intensity images. These images highlighted temporal changes of the distribution area, perimeter, flow distance, included angle, and collapse direction. To validate the image-processing results, reflectance spectra of the rock samples collected after the eruption in June 2006 were measured in a laboratory. The reflectance spectra of all samples showed similar characteristics to the reference spectra, which were derived from atmospheric correction of Hyperion sensor image data covering the lava dome at the summit. Therefore, P-zones were confirmed to be the pyroclastic flow deposits originating from destruction of the lava dome at the summit. The image-processing results clarified that the extent of the distribution areas, perimeter, flow distances, and included angle of the P-zones were variable among the eruptions, while the collapse direction had a constant pattern. The collapse pattern followed a clockwise change from the south toward the west. By comparing the ratio maps of Bouguer gravity anomaly data in two periods, the change was interpreted to originate from the inclination of the conduit and the formation of shallow and deep magma reservoirs. 相似文献
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This study presents a new geostatistical approach to characterization of the geometry and quality of a multilayer coal deposit using the data of seam thickness as a geometric property and the contents of ash, sodium, total sulphur, and the heating value as quality properties. A coal deposit in East Kalimantan (Borneo), Indonesia, which has a synclinal geological structure, was chosen as the study site. Semivariogram analysis clarified the strong dependence of heating value on ash content in the top and bottom parts of each seam and the existence of a strong correlation with sodium content over the sub-seams in the same location. The correlations between the geometry and quality of the seams were generally weak. A linear coregionalization model was used to derive the spatial correlation coefficients of two variables at each scale component from the single- and cross-semivariogram matrices. Because the data were correlated spatially in the same seam or over different seams, multivariate techniques (ordinary cokriging and factorial cokriging) were mainly used and the resultant spatial estimates were compared to those derived using a univariate technique (ordinary kriging). A factorial cokriging was effective to decompose the spatial correlation structures with different scales. Another important characteristic was that the sodium content shows distinct segregation: the low zones are concentrated near the boundary of the sedimentary basin, while the high zones are concentrated in the central part. The main component of sodium originates from the abundance of saline water. Therefore, it can be inferred that seawater had stronger effects on the coal depositional process in the central basin than in the border part. The geostatistical modeling results suggest that the thicknesses of all the major seams were controlled by the syncline structure, while the coal qualities chiefly were originated from the coal depositional and diagenetic processes. 相似文献
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Liu Chunxue Kubo Taiki Lu Lei Koike Katsuaki Zhu Wenjie 《Natural Resources Research》2019,28(1):99-108
Natural Resources Research - Fracture is an important factor controlling mineralization and ore distribution in metallic deposits. Fracture also affects mechanical stability of drifts. A plausible... 相似文献
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Precise spatial estimation of ore grades and impurity contents from sample data limited in amount and location is indispensable
to metallic and nonmetallic resource exploration. One of the advantages of using geostatistics for this purpose is that it
can incorporate multivariate data into spatial estimation of one variable. However, there are two weak points concerning technical
and post-processing problems. First is the difficulty in application to geologic data in which spatial correlations are not
clear because of intrinsic nonlinear behavior. Second is the absence of indices to interpret the mechanisms and factors which
govern the spatial distribution. To address these problems, a spatial method of modeling based on a feedforward neural network,
SLANS, which recognizes the relationship between the data value and location by considering supplementary attributes such
as lithology and biostratigraphy, and a sensitivity analysis using this network were developed. These methods were applied
to two case studies, genetic mechanisms of kuroko deposits and quality assessment of a limestone mine. The first case study
is a spatial analysis of principal metals of kuroko deposits (volcanogenic massive sulfide deposits) in the Hokuroku district,
northern Japan. It was clarified that upward and downward sensitivity vectors were distinguished near the deposits inside
and outside the tectonic basin, respectively. Sensitivity analysis for the second case study showed a strong effect of crystalline
limestone on the important impurity, P2O5 contents. Hydrothermal alteration, which could cause leaching and secondary concentration of phosphorus, is considered to
have produced this effect. 相似文献
8.
Katsuaki Koike Yoshihiro Shiraishi Eduardo Verdeja Kenji Fujimura 《Mathematical Geology》1998,30(6):733-759
In Japan, many major cities are located on tectonic basins which are surrounded by faults and underlain by soft alluvial materials. Because these areas are subject to earthquake damages, it is important to determine their seismic engineering characteristics. Geotechnical databases which contain many borehole logs are useful information sources for this type of analysis. Each datum stored in the database has a value or an attribute, and its location is irregular in both horizontal and vertical directions. A new interpolation method based on the optimization principle is proposed here to deal with such three-dimensionally distributed data. Susceptibility of unconsolidated ground to liquefaction is known to be related to the content of loose and saturated sand. The mixture ratio of several soil types in a deposit, i.e., granular composition, is strongly influenced by the sedimentary environment. There are two numerical methods: the optimization principle method (OPM) used to determine three-dimensional distribution of granular composition and the model used to evaluate liquefaction. The application of the proposed methods to two locations in Japan indicated that the zones with high susceptibility to liquefaction were indeed those that had suffered from liquefaction during past earthquakes. 相似文献
9.
Neural Network-Based Estimation of Principal Metal Contents in the Hokuroku District,Northern Japan,for Exploring Kuroko-Type Deposits 总被引：7，自引：0，他引：7
Koike Katsuaki Matsuda Setsuro Suzuki Toru Ohmi Michito 《Natural Resources Research》2002,11(2):135-156
The Hokuroku district, extending over 40 × 40 km2 in northern Japan, is known to be dominated by kuroko-type massive sulfide deposits that have a genetic relation to submarine volcanic activity. The deposits are hosted in a specific stratigraphic zone of Miocene volcanic rocks. Because kuroko-type deposits are under exploration in several countries, it is important to integrate the geologic and geochemical data that have been accumulated in the Hokuroku district to characterize the distribution of deposits and produce a map of mineral potential. Thus, we collected data on multiple chemical components from 1917 rock cores at 143 drillhole sites and concentrated on components with relatively large amounts of data, which are SiO2, Al2O3, and Fe2O3 as major elements and Cu, Pb, and Zn as trace elements. Although frequencies of these data can be approximated by normal or lognormal distributions, spatial correlation structures cannot be extracted from the semivariograms of each component nor from the cross-semivariograms between two components of the major or minor elements. To handle such complexity, a spatial method of modeling content distribution, SLANS, is developed by applying a feedforward neural network. The principle of SLANS is to train a network repeatedly to recognize the relation between the data value and the location and lithology of a sample point. One-hundred outputs for each element are obtained by changing the numbers of neurons in a middle layer from 1 to 10 and sample data used for training from 3 to 12, and finally one output is selected based on the estimation precision of the network which is restricted near the target point. After constructing a geologic distribution model from the geological column classified into 25 rock codes, three-dimensional distributions of Cu, Pb, and Zn contents are estimated over the study area. The content models are considered to be valid because high-content zones are located on the known mine sites and the margins of ancient volcanoes or calderas. Some zones are distributed along strikes of major deep-seated fractures in the district. 相似文献
10.
Identifying groundwater arsenic contamination mechanisms in relation to arsenic concentrations in water and host rocks 总被引：1，自引：1，他引：0
Leaching and oxidation of high arsenic (As) host rocks tend to be induced by circulation of deep geothermal waters, which
increase As concentration in shallow groundwater. The purpose of this study is to identify the mechanism of groundwater As
contamination in relation to leaching and oxidation along the border between the South Minahasa and Bolaang Mongondow districts,
North Sulawesi, Indonesia. This region contains Miocene sedimentary rock-hosted disseminated gold deposits associated with
hydrothermal alteration in a fault zone. Abnormally high As concentrations were observed in hot and cold springs and in surrounding
shallow groundwater for a total mineralization area of 8 × 10 km2. Two methods were adopted in this study: (1) microscopic and spectroscopic analyses of rock samples for mineral identification
and (2) geostatistics for spatial modeling of As concentrations in groundwater. Jarosite was identified as the chief fill
mineral in rock defects (cracks and pores). The presence of this mineral may indicate release of As into the environment,
as can occur as an alteration product derived from oxidation and leaching of pyrite, As-rich pyrite or sulfide minerals by
geothermal waters. Moreover, As concentrations in groundwater were estimated using geostatistics for spatial modeling. The
co-kriging map identified local anomalies in groundwater As concentrations over the permissible limit (10 ppb). Such anomalies
did not appear through ordinary kriging. Integration of the results indicates that As contamination in shallow groundwater
probably is controlled by heterogeneous distributions of jarosite and variations in intensity and extent of hydrothermal activities. 相似文献