Title :
Application of Information Fusion Method Based on Generalized Regression Neural Network in Hydrocarbon Reservoir Evaluation Studies
Author_Institution :
Sch. of Comput. Sci., Yangtze Univ., Jingzhou, China
Abstract :
Identify the hydrocarbon reservoir quickly and accurately under complex geological environment which is an important field of academic research at home and abroad. This paper presents an information fusion method based on Generalized Regression Neural Network (GRNN) which solves the problem of the low recognition accuracy and efficiency in the exploration of hydrocarbon reservoir. Through a practical example compared with BP neural network in the hydrocarbon reservoir identification results, indicating that the information fusion method based on GRNN has the advantages of simple structure, quick convergence, and accurate prediction. The information fusion method based on GRNN has broad application prospects in hydrocarbon reservoir identification.
Keywords :
hydrocarbon reservoirs; mining industry; neural nets; regression analysis; generalized regression neural network; geological environment; hydrocarbon reservoir evaluation; hydrocarbon reservoir identification; information fusion; Accuracy; Biological neural networks; Decision making; Feature extraction; Hydrocarbon reservoirs; Sensors; Training; Information fusion; Log Evaluation; Multi-sensor; Neural network;
Conference_Titel :
Genetic and Evolutionary Computing (ICGEC), 2011 Fifth International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4577-0817-6
Electronic_ISBN :
978-0-7695-4449-6
DOI :
10.1109/ICGEC.2011.89