Abstract: Logistic model is one of the most accepted prediction models, but its utilization in predicting natural gas production is often limited due to its intrinsically fixed environment threshold and population growth rate. In this paper, these two parameters are functionalized to be time-dependent according to the characteristics of natural gas production. Based on singular perturbation theory, the matching expansion method is applied to solve this time-dependent Logistic prediction model. China’s natural gas production is used as an empirical case, and comparisons between traditional prediction models are conducted. Results reveal that the developed Logistic model can effectively improve the prediction, and according to this model, China’s natural gas production will reach the peak of 331.13 billion cubic meters by 2028.

Key words: improved Logistic model, singular perturbation, matched expansion method, natural gas, production prediction