Prediction of Coalbed Methane Production in China Based on an Optimized Grey System Model

Bo Zeng · Hui Li

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Grey System Theory Applications Forecasting Techniques and Applications Coal Properties and Utilization

Abstract

Coalbed methane (CBM) is one of the three major sources of unconventional natural gas. Accurate prediction of CBM production is an important basis for the governmental decision-making in the exploitation intensity of CBM resources and related energy policies. In this study, the new action quantity k 2 d and r -order were introduced into the traditional three-parameter discrete grey forecasting model. The action quantity k 2 d was used to deal with the simulation of data with more complicated characteristics, and r -order was used to improve the model’s dynamic adjustability in practical problems. On the basis of this, a dynamic adaptive four-parameter discrete grey forecasting model suitable for forecasting CBM production was constructed and derived. Then the new model was applied to simulate China’s CBM ground production. The results show that the comprehensive mean relative percentage error of the new model was 0.4765%, and the simulation accuracy was grade I, indicating its performance was superior to other mainstream grey forecasting models. Finally, the new model was employed to predict China’s CBM ground production from 2019 to 2023, and relevant suggestions were put forward accordingly. The research provides a reference basis for the Chinese government to formulate CBM import policies and optimize energy structure, as well as a feasible modeling method for the prediction of CBM production in the future.

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References

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