关键词: 天然气水合物, 灰色理论, BP神经网络, 差值结合法, 马尔科夫链模型

Abstract: Natural gas hydrate has the advantages of high gas storage rate, low pollution and large reserves, which has good prospects for development. In addition, natural gas hydrates formed in the process of natural gas processing and transportation will lead to the problem of serious such as pipeline blockage. Therefore, it is of practical significance to analyze and predict the formation of natural gas hydrate. In order to predict the formation of natural gas hydrate, aiming at the merits and demerits of previous research on the prediction methods of natural gas hydrate formation, the combination model of GM (1,1) theory and Back Propagation neural network is established by using MATLAB computer language, which is based on the artificial neural network with the ability to solve complex system problem.Considering the improvement of prediction accuracy, the difference combination method is used to combine the two methods. The GM (1,1), back propagation neural network and the combined model are used to predict and compare the pressure data obtained in the experiment. In order to further verify the accuracy of the combined model, Markov chain model is selected for the prediction test. The results show that the combined model of GM（1,1）and BP neural network has higher canprecision and this method can be widely used in many directions, which can provide a theoretical basis for the development and utilization of NGH in the future.

Key words: Natural gas hydrate, The grey forecast, The back propagation neural network, Difference combination method, Markov chain model