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Talk · Joint International Conference on Soft Computing and Intelligent Systems and International Symposium on Advanced Intelligent Systems · November 1, 2012

Geophysical research of boreholes: Artificial neural networks data analysis

Ravil I. Mukhamediev, Yan I. Kuchin, Elena Muhamedyeva

Yan Kuchin
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Abstract

The economic indicators of the mining process depend on the speed and accuracy of geophysical data interpretation, but the process of logging data interpretation can not be strictly formalized. Therefore, computer interpretation methods on the basis of expert estimates are necessary, such as artificial neural networks (ANN) which have already been used for solving a wide range of recognition problems. The paper analyzes the quality of network's data interpretation essentially depending on its configuration parameters, methods of data preprocessing and learning samples. About 2000 calculation experiments have been made, software and templates for pre-processing of data and interpretation findings have been developed. These experiments showed the effectiveness of neural network approach to solving the problem of geological rocks recognition in stratum-infiltration uranium deposits. Further research in this area will raise the recognition process automation and its accuracy.

Geochemistry and Geologic MappingNeural Networks and ApplicationsGeoscience and Mining Technologyartificial neural networksuranium depositsdata preprocessing

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