Optimizing enhanced coalbed methane recovery in thick lignite formations: An integrated technical and economic evaluation - Zhiming Fang; Shaicheng Shen (Results in Engineering)
The Erlian Basin, characterized by extensive lignite deposits with considerable thickness, presents significant potential for coalbed methane (CBM) extraction. However, CBM exploration in lignite has received limited attention due to its typically low gas content, and the economic evolution of thick lignite reservoirs remains understudied. This study employs an integrated approach combining numerical simulation with economic evaluation to systematically assess the technical and economic feasibility of Enhanced Coalbed Methane (ECBM) recovery in thick lignite formations within the Erlian Basin of Inner Mongolia. We evaluate the economic feasibility of ECBM under various gas injection scenarios and optimize key operational parameters through a coupled neural network model and particle swarm optimization algorithm. The key findings are as follows: (1) Even with carbon sequestration benefits incorporated, CO2-ECBM projects in the Erlian Basin’s thick lignite formations remain economically unviable under current market conditions. (2) Reservoir permeability is the dominant geological parameter governing ECBM feasibility in thick lignite reservoirs. (3) The hybrid neural network–optimization algorithm demonstrates high computational efficiency in optimizing ECBM injection schemes. Optimal well spacing exhibits a strong positive correlation with reservoir permeability. The ideal CO₂ injection ratio is primarily determined by the economic balance between carbon credit pricing and CO₂ capture costs.