We have analyzed the characteristics of geological survey works of the dam foundation and the aspect of the using of geological maps for the design and construction of the dam. And proposed the improvement on the geological survey works by the computer data processing. Moreover, we have developed“Geological Mapping Support System”that has no function of the geological interpretation, but is able to support the geologist in mapping, and we report the summary of this system.

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This paper presents an application of artificial neural network system to the distribution analysis of metalliferous vein. The geological classification of excavating face and the spatial estimation of the ore body are difficult problems using conventional pattern recognition methods, because they require a large amount of statistical data. The artificial neural network has the ability to learn pattern recognition as a human being does from training data. We examined the multilayer perceptron neural network and the self-organizing Feature Map for the classification and the distribution of metalliferous veins. The digital images of the excavation face were processed by these methods, and consequently, the three dimension-al structures of gold veins are successfully estimated.

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The box-counting method, BC method, is widely used to determine the fractal dimension of self-similar structure on a plane. The basic implementation of this method is, 1) covering the object with cells, 2) counting the number of cells occupied with the object, and 3) executing the former steps about the various size of cell. The fractal dimension is easily obtained from the slope of the approximation line on the log-log graph which shows relationship between cell size and the number of cell filled with the object. The minimum and maximum cell sizes were defined as lower and upper cut-off levels in order to restrict data points for evaluating the fractal dimension. The slope of approximation line which is equivalent to the fractal dimension is calculated using the data points in the range between lower and upper cut-off levels. Computer software FIVA-Fractal Image Visual Analyzer - was developed to evaluate fractal properties and to calculate fractal dimension on the basis of BC method.
Lower and upper cut-off levels could be selected arbitrarily by FIVA and the fractal dimension was obtained from the restricted range. Optimum cut-off level was obtained by analyzing self-evident fractal objects. The lower cut-off level was larger than the resolution of object figure. The upper cut-off level was required 1/30 to the whole figure size of objects. The precision of fractal dimension calculated by FIVA was in the range from -5 to -1% on analyzing fractal objects of which resolution was smaller than 1/360. However, in the case of which those resolution was about 1/100, the precision was in the range from -11 to +5%.
The fractal dimension of space filling of natural fracture pattern was obtained from data points on the log-log plot between the lower and upper cut-off levels. The resolution of natural fracture pattern used in this study was about 1/100 to the whole pattern size, therefore, the lower cut-off level was 1/90, the upper cut-off level was 1/30. By using the results of analyzing self - evident fractal objects, the fractal dimension of space filling of a fracture pattern was expected in the range from 1.1 to 1.3.

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Integration of geophysical methods is limited by environmental and economical conditions. However, 2 or 3 methods are usually combined to solve typical geological problems, some examples of this integrated approach being presented here. Determination of the number of methods required can be substantiated quantitatively. For this purpose the amounts of obtained information or the risk of decision-making have been calculated. The developed informational and probabilistic criteria, as well as the solution of“four colors”mathematical problem, allow to divide the area under investigation into classes in accordance with the results of two independent geophysical methods. Such integration is theoretically sufficient for regioning and prospecting many important objects.

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