考虑吸附效应的页岩气传质机理及产能主控因素分析

The Mass Transfer Mechanism of Shale Gas Considering Adsorption Effect and the Main Controlling Factors of Productivity

摘要: 页岩气储层中吸附气与游离气共存，因此描述页岩基质孔内吸附行为是建立跨尺度渗流模型的关键。然而，现有吸附模型多基于单分子层吸附假设，难以适用于深层页岩气藏高温高压条件下的吸附特征，导致吸附量预测存在偏差。本文采用分子模拟方法研究甲烷在干酪根纳米孔中的吸附过程，厘清高温高压下页岩气的吸附规律。基于描述单分子层吸附、多分子层吸附和微孔吸附的吸附模型，明确描述页岩气吸附的数学模型。考虑真实气体效应、吸附效应、气体滑脱、Knudsen扩散及应力敏感效应等，建立基质孔内页岩气传质模型。通过有限元方法求解，并采用四川盆地H区块实际生产数据校验模型。结果表明吸附量与压力呈正相关，与温度呈负相关，并优选出Langmuir-Freundlich模型在温度353.15~433.15 K下预测误差最小。在此基础上，系统分析了工程因素和地质因素对气井产能的影响规律，并引入灰色关联方法定量评价各参数的重要性。研究成果可为页岩气压裂水平井的有效开发及产能评价提供一定依据。

Abstract: Adsorbed gas and free gas coexist in shale gas reservoirs, so describing the adsorption behavior is crucial for establishing a cross-scale seepage model. However, existing adsorption models are mostly based on the assumption of monolayer adsorption, making them unsuitable for the high temperature and pressure conditions in deep shale gas reservoirs, leading to deviations in adsorption capacity predictions. Therefore, molecular simulation methods are employed to study the adsorption process of methane in kerogen nanopores, and then clarify the adsorption behavior of shale gas under high temperature and pressure conditions. Based on adsorption models describing monolayer adsorption, multilayer adsorption, and micropore adsorption, a reasonable mathematical model for shale gas adsorption is identified. Considering real gas effects, adsorption effects, gas slippage, Knudsen diffusion, and stress sensitivity, a mass transfer model for shale gas in matrix pores is established. The finite element method is used to calculate gas well productivity, and the model is validated using actual production data from Block H in the Sichuan Basin. The results indicate that adsorption capacity is positively correlated with pressure and negatively correlated with temperature, and Langmuir-Freundlich model has the small prediction error within the temperature range of 353.15~433.15 K. The influences of engineering and geological factors on gas well productivity are analyzed, and the grey relational method is introduced to evaluate the importance of each parameter. This work is helpful for the effective development and productivity evaluation of shale gas reservoirs.