BP神经网络算法在陆域天然气水合物成藏预测中的应用

doi:10.11720/wtyht.2019.1277

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Abstract

During the exploration of terrestrial gas hydrates,Large quantities of geological, geophysical and geochemical data will be produced. The search for hydrate is of significance for effective combination of multi-source information with mathematical methods so as to establish a comprehensive information forecasting model. In this paper, the features which are favorable for gas hydrate accumulation were extracted from geological, geophysical and geochemical data in Muli area, and the corresponding transformation regularity was proposed. BP artificial neural network was used to do the study of gas hydrate prediction, and the effects of these two methods are compared and assessed. The results show that the prediction area is highly correlated with existing drilling result, suggesting that the methods are effective and the transformation regularity is feasible.

Key words： BP artificial neural network gas hydrate hydrate prediction Muli area

Received: 13 July 2018 Published: 31 May 2019

P631

Corresponding Authors: Xue-Qiang ZHANG E-mail: 97688628@qq.com

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	Kang-Wei FU
	Xue-Qiang ZHANG
	Yan PENG

Cite this article:

Kang-Wei FU,Xue-Qiang ZHANG,Yan PENG. The application of BP neural network algorithm to the prediction of terrestrial gas hydrate accumulation[J]. Geophysical and Geochemical Exploration, 2019, 43(3): 486-493.

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https://www.wutanyuhuatan.com/EN/10.11720/wtyht.2019.1277 OR https://www.wutanyuhuatan.com/EN/Y2019/V43/I3/486

Neuron model

Basic structure of neural network

Schematic diagram of fault in Muli area

Prediction error result of different number of neurons in the hidden layer

Grid point sample with missing data items

Sample table

Prediction chart of hydrate accumulation possibility based on BP neural network

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