Correlating mass physical properties with ALOS reflectance spectra for intertidal sediments from the Ba Lat Estuary (northern Vietnam): an exploratory laboratory study

Characterization of the sediment composition of tidal flats and monitoring of their spatiotemporal changes has become an important part of the sustainable management of coastal environments. To accurately classify sediments through remote sensing, a comprehensive understanding of sediment reflectance spectra is indispensable. The present laboratory-based study explores the performance of the high spatial resolution (10?×?10 m) Advanced Land Observing Satellite (ALOS) launched in 2006. Relationships between reflectance spectra (bands 1 to 4) and four typical mass physical properties were investigated under wet and dry experimental conditions for intertidal sediments sampled near the Ba Lat Estuary in northern Vietnam. Reflectance in the near-infrared region corresponding to ALOS band 4 (0.76–0.89 μm) was found (1) to have a strong negative correlation with sand content (dry wt%) under both wet and dry conditions (linear correlation coefficient r?=?–0.7859 and –0.8094, respectively), (2) to increase with decreasing relative water content (%) in a given sediment type (r?=?–0.7748 to –0.9367 for mud, sandy mud, muddy sand, and sand), (3) to have a positive correlation with organic matter content (r?=?0.7610 and 0.6460 under wet and dry conditions for contents >0.20 dry wt%), and (4) to be insignificantly correlated with mineral composition assessed in terms of contents (wt%) of quartz, clay minerals, and mica group minerals. Positive relationships between reflectance and water content for the pooled data of all sediment types (r?=?0.6395) or organic matter content contrast with previous findings, and can be attributed to close interrelationships between these properties and the predominance of sand content as controlling factor of reflectance. This study clarifies that ALOS band 4 provides the most useful imagery for intertidal monitoring because its reflectance, as simulated using the laboratory data, shows the strongest correlation with sand content. In a next step, these experimental findings should be verified by identifying the reflectance relationships at satellite image scales, and also considering the effects of other tidal flat features on reflectance, such as microtopography and biological surface characteristics.     

Spatial Simulation and Characterization of Three-Dimensional Fractures in Gejiu tin District,Southwest China,Using GEOFRAC

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...     

Identifying spatial heterogeneity of coal resource quality in a multilayer coal deposit by multivariate geostatistics

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.     

Neural Network-Based Estimation of Principal Metal Contents in the Hokuroku District,Northern Japan,for Exploring Kuroko-Type Deposits

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.     

Introduction to the Special Issue on the “Mathematical Geology for Resource Exploration” Session at IGC32

Natural Resources Research -     

Geostatistical Modeling of Ore Grade Distribution from Geomorphic Characterization in a Laterite Nickel Deposit

Due to growing consumption of nickel (Ni) in a range of industries, the demand for Ni has increased rapidly around the world. This trend requires a more precise estimation of available Ni grade deposits and an identification of factors controlling the grade distribution. To achieve these requirements, this study applies geostatistical techniques to spatial modeling of the Ni grade in a laterite Ni deposit, with reference to geomorphic features such as slope gradient and the thickness of limonite and saprolite zones. The Sorowako area in Sulawesi Island, Indonesia, was chosen as a case study area because it has a representative laterite Ni deposit with large reserves. Chemical content data from drillhole cores at 294 points were used for the analysis. The slope gradient was found to have a remarkable correlation with the thickness of the limonite zone, but there was no correlation between the thickness of the limonite and the saprolite zones above the bedrock. One important feature was a general correlation between the thickness of the saprolite zone and the maximum Ni grade in this zone: the grade increases with the thickness of the zone. Co-kriging was adopted to incorporate this correlation into estimating the maximum Ni grade in the saprolite zone. As a result, the maximum Ni grade in the saprolite zone tends to be high mainly in areas of slight slope. The Ni accumulation at this topographic feature probably originates from deep weathering by groundwater infiltrating through well-developed rock fractures.     

Detection and hydrologic modeling of aquifers in unconsolidated alluvial plains through combination of borehole data sets: a case study of the Arao area, Southwest Japan

In addition to spatial distribution of groundwater-flow parameters, aquifer properties of location and shape are also significant for assessing groundwater resources because they strongly affect water flow. We present a selection of geologic data suitable for aquifer analysis, a mathematical method of processing them, and a combination of several maps produced by it. The data used in the analysis are typically obtained by borehole investigation. Our targets are the areas underlain by geologic bodies with different ages and lithologies; the spatial correlation structures of geologic data over the areas tend to change locally. The processing method should be a versatile one that is applicable to areas where geostatistical stationarity is not satisfied. The aquifer analysis consistent with that requirement consists of two steps: the first is the transformation of screen locations, locations of sand and gravel layers, and resistivity by electric logging into indicator values, and the second is three-dimensional interpolation of these using the optimization principle method to produce three kinds of distribution models. A stochastic simulation is also used for modeling the resistivity distribution. The three distribution models are integrated to generate a value for evaluating the possibility of aquifer existence. A case study of an alluvial coastal plain, situated in southwest Japan, describes an aquifer model that contains three permeable layers. Each layer has about 10-m thickness and is lens shaped. To confirm the validity of the model, we have drilled two wells that reached one of the middle and bottom permeable layers, observing the water level change. Low correlation of the temporal changes of levels between the wells indicates that the two layers are hydrologically independent of each other. Additionally, groundwater-flow patterns have been estimated by transforming the simulation model parameter into hydraulic conductivity through a simple function and using a finite difference method for flow analysis. The procedure proposed by this study can be applied to other areas by changing the weights assigned to each geologic and geotechnical factor in the generation of the coefficient for aquifer existence, considering the reliability of each factor and hydrologic properties of study area.     

Application of Magnetotelluric (MT) Resistivity to Imaging of Regional Three-Dimensional Geologic Structures and Groundwater Systems

Widespread definition of a groundwater system in three dimensions is necessary for the management and maintenance of groundwater resources. A magnetotelluric (MT) survey can be an effective geophysical prospecting method for imaging regional geological structures by measuring both shallow and deep resistivity. To demonstrate the capability of an MT survey to characterize a groundwater system, the Kumamoto area of central Kyushu in southwestern Japan was selected as a case study site because of its rich groundwater resources. Three-dimensional (3D) MT resistivity structure to a depth of 5?km was modeled by 1D inversion analysis of raw MT data and 3D interpolation of the resultant resistivity column data by the optimization principle method. Consequently, both deep and shallow aquifers were detected. A high-resistivity zone appears at depths between 500 and 2,000?m between the Futagawa?CHinagu faults and the Usuki?CYatsushiro tectonic line, which supports the existence of an aquiclude under the aquifer. The most important characteristic inferred from the 3D resistivity model is that the deep groundwater system below a depth of 1,000?m has two main flow paths. One path is likely to be through porous rocks because the low resistivity zone is regarded as tuff with sand and gravel, and the other flow path is interpreted to be through fractured zones along the Hinagu faults. Hence, the path and direction of the groundwater flows are probably controlled by geologic structures and the configuration of the active faults. These findings support the effectiveness of the MT method for investigating groundwater systems.     

Hydrogeologic-structure and groundwater-movement imaging in tideland using electrical sounding resistivity: a case study on the Ariake Sea coast, southwest Japan

Groundwater flow exerts a crucial control on the boundary between the sea and freshwater and is thus a key factor for preserving groundwater resources and preventing seawater intrusion in coastal areas. Although it is highly probable that geological faults in coastal areas affect groundwater flow patterns, the effect has not been described yet in detail. This study is aimed at detecting and imaging groundwater flow and its temporal change around a fault in a coastal area through resistivity and chargeability distributions using electrical sounding. The Okoshiki area in central Kyushu, southwest Japan, was selected as a case study area, because of the presence of Kamiouda Fault. The measurements were conducted along six lines of both parallel and perpendicular orientations to the coastline. A feature suggesting a fault zone was evident on two lines. Through the temporal change of resistivity, movement and mixing processes of the seawater and freshwater during the ebb, low and flood tides were interpreted. A conceptual model of the processes was constructed in which a fault zone and the configuration of bedrock are dominant elements by acting as a selective path and a barrier to the groundwater flow, respectively.     

Evaluation of Interpolation Accuracy of Neural Kriging with Application to Temperature-Distribution Analysis

An interpolation method based on a multilayer neural network (MNN), has been examined and tested for the data of irregular sample locations. The main advantage of MNN is in that it can deal with geoscience data with nonlinear behavior and extract characteristics from complex and noisy images. The training of MNN is used to modify connection weights between nodes located in different layers by a simulated annealing algorithm (one of the optimization algorithms of the network). In this process, three types of errors are considered: differences in values, semivariograms, and gradients between sample data and outputs from the trained network. The training is continued until the summation of these errors converges to an acceptably small value. Because the MNN trained by this learning criterion can estimate a value at an arbitrary location, this method is a form of kriging and termed Neural Kriging (NK). In order to evaluate the effectiveness of NK, a problem on restoration ability of a defined reference surface from randomly chosen discrete data was prepared. Two types of surfaces, whose semivariograms are expressed by isotropic spherical and geometric anisotropic gaussian models, were examined in this problem. Though the interpolation accuracy depended on the arrangement pattern of the sample locations for the same number of data, the interpolation errors of NK were shown to be smaller than both those of ordinary MNN and ordinal kriging. NK can also produce a contour map in consideration of gradient constraints. Furthermore, NK was applied to distribution analysis of subsurface temperatures using geothermal investigation loggings of the Hohi area in southwest Japan. In spite of the restricted quantity of sample data, the interpolation results revealed high temperature zones and convection patterns of hydrothermal fluids. NK is regarded as an interpolation method with high accuracy that can be used for regionalized variables with any structure of spatial correlation.