A parallel compositional reservoir simulator for large-scale CO2 geological storage modeling and assessment

被引:0
|
作者
Di, Chaojie [1 ,2 ]
Wei, Yizheng [2 ]
Wang, Kun [3 ]
Liu, Benjieming [1 ]
Deng, Peng [1 ]
Sun, Zhe [1 ]
Lei, Xuantong [1 ]
Chen, Zhangxin [1 ,4 ]
机构
[1] University of Calgary, 2500 University Dr NW, Calgary,AB, Canada
[2] Computer Modelling Group Ltd., 3710 33 St NW, Calgary,AB, Canada
[3] Amazon.com, Inc., 40 King St W 47th floor, Toronto,ON, Canada
[4] Eastern Institute of Technology, 568 Zhuangshi St, Zhenhai District, Zhejiang, Ningbo, China
关键词
Aerodynamics - Parallel processing systems - Petroleum reservoir evaluation;
D O I
10.1016/j.scitotenv.2024.177065
中图分类号
学科分类号
摘要
Storing CO2 in deep aquifers and depleted gas reservoirs is an effective way to achieve carbon neutrality. However, the numerical simulation of CO2 storage in these formations is challenging due to the complexity of gases-brine systems. The number of gas species included in the gases-brine fluid models of existing simulators cannot meet the rapidly evolving CO2 sequestration scenarios. To address this intricate issue, we developed a three-dimensional fully implicit parallel CO2 geological storage simulator (PRSI-CGCS) on distributed-memory computers based on our in-house parallel platform. This simulator uses a compositional fluid model with a diverse range of gas species, including CO2, C1 ~ C3, N2, H2S, as well as newly added gases H2 and O2, which may be encountered in geological CO2 storages. Besides, we provide more suitable scaling factors for different gases in the stability analysis bypassing (SAB) method to accelerate the gases-brine phase equilibrium calculations. PRSI-CGCS does not incorporate energy conservation equations, and salt precipitation or dissolution is also not considered. Numerical experiments show that our simulator is scalable, robust and validated to simulate large-scale CO2 storage problems with hundreds of millions of grid blocks on a parallel supercomputer cluster. Besides, after our modification on scaling factors, the SAB method can reduce the number of stability analyses by 61.39 % to 88.71 %, thereby reducing simulation time. Furthermore, case studies indicate that injecting O2 and H2 along with CO2 reduces the stability or capacity of CO2 storage and increases the pressure required for injection. However, this impact is not significant when the impurity content is less than 10 %. © 2024 The Authors
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