基于Maxwell-Stefan双扩散模型的煤层气注气数值模拟

目前煤层气注气数值模拟软件中均以扩展Langmuir模型模拟多组分气体吸附/解吸,以拟稳态单孔扩散模型和Fick定律描述煤层基质中气体扩散,虽然简单,便于应用,但存在较大局限性。以试验数据为依据,评价扩展Langmuir、IAS和2D PR-EOS多组分气体吸附模型可靠性,并建立Maxwell-Stefan双扩散模型模拟气体扩散过程。最后,将双扩散模型与煤储层气水两相多组分渗流模型耦合,利用IMPES方法求解研究煤层气注气过程。研究表明:2D PR-EOS模型预测结果优于扩展Langmuir和IAS模型;注气初期基质中多组分气体吸附和甲烷解吸速率较快,之后逐渐变缓;该模拟方法可以较为准确地模拟煤层气衰竭和注气开发过程,预测煤基质中气体各组分浓度分布,为煤层气注气开发的研究及现场应用提供有效的技术手段。

Numerical simulation of gas injection enhanced coalbed methane recovery based on bi-dispersing diffusion model with Maxwell-Stefan equation

In most commercial coalbed methane simulation software, an extended Langmuir model, quasi-steady single pore diffusion and Fick ''s law are currently used to describe the adsorption of mixed gases on coal rocks and gas diffusion process. Although these methods are simple and easy for application, there are also some limitations. In this paper, the effectiveness of the extended Langmuir, IAS and 2D PR-EOS models for the prediction of the gas adsorption process on coal was analyzed with experimental data in order to establish a better model for the simulation. Then, the Maxwell-Stefan equation was used to develop a bi-dispersing diffusion model, in which the 2D PR-EOS model was used to predict multi-component gas adsorption. Finally, the bi-dispersing diffusion model was coupled with a gas/water two-phase multi-component simulation model, and the IMPES method was used to solve the equations. The simulation results of gas injection for enhanced coalbed methane recovery using CO₂ and N₂ show that the 2D PR-EOS model is better than the extended Langmuir and IAS models, which can reflect the relative adsorption of multi-component gases. The adsorption and desorption rates of gases are faster in the early stage of the gas injection, then gradually become slow, and the adsorption rate of CO₂ is significantly higher than that of N₂. This numerical simulation method can effectively simulate the gas injection process for enhanced methane recovery, and accurately predict the distribution of different gas components in the coal matrix.