Modeling natural gas compressibility factor using a hybrid group method of data handling

被引:30
|
作者
Hemmati-Sarapardeh, Abdolhossein [1 ,2 ]
Hajirezaie, Sassan [3 ]
Soltanian, Mohamad Reza [4 ]
Mosavi, Amir [5 ,6 ]
Nabipourg, Narjes [7 ]
Shamshirband, Shahab [8 ,9 ]
Chau, Kwok-Wing [10 ]
机构
[1] Shahid Bahonar Univ Kerman, Dept Petr Engn, Kerman, Iran
[2] Jilin Univ, Coll Construct Engn, Changchun, Jilin, Peoples R China
[3] Princeton Univ, Dept Civil & Environm Engn, Princeton, NJ 08544 USA
[4] Univ Cincinnati, Dept Geol, Cincinnati, OH USA
[5] Obuda Univ, Kando Kalman Fac Elect Engn, Budapest, Hungary
[6] Oxford Brookes Univ, Sch Built Environm, Oxford, England
[7] Duy Tan Univ, Inst Res & Dev, Da Nang, Vietnam
[8] Ton Duc Thang Univ, Dept Dept Management Sci & Technol Dev, Ho Chi Minh City, Vietnam
[9] Ton Duc Thang Univ, Fac Informat Technol, Ho Chi Minh City, Vietnam
[10] Hong Kong Polytech Univ, Dept Civil & Environm Engn, Hung Hom, Hong Kong, Peoples R China
关键词
Group method of data handling (GMDH); natural gas compressibility factor; big data; correlation; equations of state (EOSs); data-driven model; artificial intelligence (AI); EQUATION-OF-STATE; GAS/VAPOR VISCOSITY; PRECIPITATION; SIMULATION; PREDICTION; DENSITY; FLUIDS; FLOW;
D O I
10.1080/19942060.2019.1679668
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The natural gas compressibility factor indicates the compression and expansion characteristics of natural gas under different conditions. In this study, a simple second-order polynomial method based on the group method of data handling (GMDH) is presented to determine this critical parameter for different natural gases at different conditions, using corresponding state principles. The accuracy of the proposed method is evaluated through graphical and statistical analyses. The method shows promising results considering the accurate estimation of natural gas compressibility. The evaluation reports 2.88% of average absolute relative error, a regression coefficient of 0.92, and a root means square error of 0.03. Furthermore, the equations of state (EOSs) and correlations are used for comparative analysis of the performance. The precision of the results demonstrates the model?s superiority over all other correlations and EOSs. The proposed model can be used in simulators to estimate natural gas compressibility accurately with a simple mathematical equation. This model outperforms all previously published correlations and EOSs in terms of accuracy and simplicity.
引用
收藏
页码:27 / 37
页数:11
相关论文
共 50 条
  • [41] A Methodology for Calculating the Natural Gas Compressibility Factor for a Distribution Network
    Cezar de Almeida, J.
    Velasquez, J. A.
    Barbieri, R.
    [J]. PETROLEUM SCIENCE AND TECHNOLOGY, 2014, 32 (21) : 2616 - 2624
  • [42] Equations for the Z-factor and Compressibility of Nigerian Natural Gas
    Ohirhian, P. U.
    [J]. ADVANCES IN MATERIALS AND SYSTEMS TECHNOLOGIES II, 2009, 62-64 : 484 - 492
  • [43] A novel correlation approach for prediction of natural gas compressibility factor
    Ehsan Heidaryan
    Amir Salarabadi
    Jamshid Moghadasi
    [J]. Journal of Energy Chemistry, 2010, 19 (02) : 189 - 192
  • [44] A novel correlation approach for prediction of natural gas compressibility factor
    Heidaryan, Ehsan
    Salarabadi, Amir
    Moghadasi, Jamshid
    [J]. JOURNAL OF NATURAL GAS CHEMISTRY, 2010, 19 (02): : 189 - 192
  • [45] Experimental Determination of the Compressibility Factor of Natural Gas: Methods and Results
    D. Y. Kutovoy
    I. A. Yatsenko
    V. B. Yavkin
    A. N. Mukhametov
    P. V. Lovtsov
    R. I. Ganiev
    [J]. Measurement Techniques, 2021, 64 : 737 - 743
  • [46] Hybrid physical and data driven transient modeling for natural gas networks
    Su, Lei
    Zhao, Jun
    Wang, Wei
    [J]. JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING, 2021, 95
  • [47] Evaluation of Correlations of Compressibility Factor (z) of Natural Gas for Algerian Gas Reservoirs
    Sidrouhou, H. M.
    Korichi, M.
    Dada, S.
    [J]. TECHNOLOGIES AND MATERIALS FOR RENEWABLE ENERGY, ENVIRONMENT AND SUSTAINABILITY (TMREES), 2019, 157 : 655 - 669
  • [48] Hourly solar irradiation forecast using hybrid local gravitational clustering and group method of data handling methods
    Benmouiza, Khalil
    [J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (40) : 60792 - 60810
  • [49] Hourly solar irradiation forecast using hybrid local gravitational clustering and group method of data handling methods
    Khalil Benmouiza
    [J]. Environmental Science and Pollution Research, 2022, 29 : 60792 - 60810
  • [50] Using group method of data handling to model customer choice behaviour
    Zhu, B.
    He, C. H.
    Niu, Y.
    [J]. SCIENTIA IRANICA, 2014, 21 (03) : 1051 - 1060