Application of BP neural network to sedimentary micro-facies identification
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Abstract
A method of sedimentary micro-facies identification based on logging data and BP neural network was proposed in this paper. Through deeply exploring limited logging data, sedimentological sample indexes were gained and the utilization rate of logging data was improved. A series of experiments were conducted in order to find the optimization criterion of the BP artificial neural network and a growing network training method was put forward. Finally, a actual case of net training and micro-facies identification by using sample set and natural samples was analyzed, which showed an accuracy ratio for 83% and realized both high efficiency and precision of micro-facies identification.
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