Prediction, analysis and suggestions of shale gas production in China based on a new grey model with four parameters

Abstract

Accurate prediction of shale gas production is important for the government to formulate energy policies. China’s shale gas production is characterized by limited data and unclear influencing factors. Grey prediction models hold advantages in solving problems with inadequate data and insufficient information. However, existing grey models for shale gas production prediction have drawbacks of insufficient characteristic expression and parameter optimization. Therefore, a new grey model with four parameters is proposed in this work. Firstly, the power index, accumulative order, and background value coefficient in the new model are optimized using the PSO algorithm. Then, based on an in-depth analysis of the model structure and tests using random samples, the new model’s compatibility and adaptability are demonstrated to be better than other similar grey models. Thirdly, the new model is applied to simulate China’s shale gas production. The results show that the comprehensive error of the new model is only 1.3626%, lower than that of the SGGM(1,1) and UGM(1,1) models, which are 1.6211% and 1.6575% respectively. Lastly, using the new model, China's shale gas production is predicted, which is expected to reach 752 hundred million cubic meters by 2030. After analyzing the rationality of the result, relevant suggestions are put forward.