Affiliations: [a] School of Economics and Management, Wuhan University, Hubei, China
| [b] Economic Development Research Centre, Wuhan University, Hubei, China
| [c] Carroll School of Management, Boston College, MA 02467, United States
| [d] School of Tourism & Research Institute of Human Geography, Xi’an International Studies University, Shaanxi, China
Correspondence:
[*]
Corresponding author. Hu, Hui, Economic Development Research Centre, Wuhan University, Hubei 430072, China. E-mail: [email protected].
Abstract: Under the influence of COVID-19, the economic benefits of shale gas development are greatly affected. With the large-scale development and utilization of shale gas in China, it is increasingly important to assess the economic impact of shale gas development. Therefore, this paper proposes a method for predicting the production of shale gas reservoirs, and uses back propagation (BP) neural network to nonlinearly fit reservoir reconstruction data to obtain shale gas well production forecasting models. Experiments show that compared with the traditional BP neural network, the proposed method can effectively improve the accuracy and stability of the prediction. There is a nonlinear correlation between reservoir reconstruction data and gas well production, which does not apply to traditional linear prediction methods
Keywords: Back propagation neural network, shale gas exploitation, economic benefit, COVID-19
