摘要
传统的统计热力学模型假设天然气水合物为理想固体溶液,同时忽略了极性水分子之间的氢键缔合作用,在预测高压条件下的水合物生成条件时偏差较大。针对这一问题,提出了基于CSM模型与CPA状态方程计算高压天然气水合物生成条件的新方法。基于该方法计算的5种高压天然气水合物生成条件与实验数据的对比表明:当水合物生成压力低于20MPa时,水合物生成压力计算值与实验值之间的平均相对偏差范围为0.59%—5.24%;当压力范围为20—69.84MPa时,计算值的平均相对偏差范围为0.79%—6.76%,显著优于CSM模型结合SRK状态方程的计算结果。预测高压条件天然气水合物生成条件时,需要同时考虑水合物溶液的非理想性和水分子之间氢键缔合作用。
The traditional statistical thermodynamic model assumes that natural gas hydrate is an ideal solid solution, and ignores the hydrogen bonding interactions between polar water molecules, resulting in large bias for the predictions on hydrate formation conditions at high pressures. In view of this problem, a new method for predicting the hydrate formation conditions of high pressure natural gas was proposed based on CSM (Colorado School of Mines) model and CPA (Cubic-Plus-Association) equation of state. Then, the hydrate formation conditions for five natural gases calculated from this method were compared with the experimental data. The results show that when the hydrate formation pressure is lower than 20 MPa, the average relative deviation ( ARD ) between the calculated hydrate formation pressures and the experimental values is 0.59%-5.24%. When the pressures range from 20 MPa to 69.84 MPa, ARD is from 0.79% to 6.76%.These results are obviously superior to those calculated from the combination of CSM model and SRK (Soave-Redlich-Kwong) equation of state. The results also demonstrate that both the non-ideality of the hydrate solution and the hydrogen bonding interactions between water molecular should be considered in the hydrate formation predictions for high pressure natural gases.
作者
杨帆
贾文龙
孙欧阳
李长俊
李明红
YANG Fan;JIA Wen-long;SUN Ou-yang;LI Chang-jun;LI Ming-hong(School of Petroleum Engineering, Southwest Petroleum University, Chengdu 610500, Sichuan Province, China;PetroChina West East Gas Pipeline Company, Shanghai 200122, China;PetroChina Southwest Pipeline Company, Chengdu 610000, Sichuan Province, China)
出处
《化学工程》
CAS
CSCD
北大核心
2019年第7期30-34,共5页
Chemical Engineering(China)
基金
国家自然科学基金青年科学基金项目(51504206),国家自然科学基金研究项目(51674213,51474184)