Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81731
Title: Modeling natural gas compressibility factor using a hybrid group method of data handling
Authors: Hemmati-Sarapardeh, A
Hajirezaie, S
Soltanian, MR
Mosavi, A
Nabipourg, N
Shamshirband, S
Chau, KW 
Keywords: Group method of data handling (GMDH)
Natural gas compressibility factor
Big data
Correlation
Equations of state (EOSs)
Data-driven model
Artificial intelligence (AI)
Issue Date: 2020
Publisher: Taylor & Francis
Source: Engineering applications of computational fluid mechanics, 2020, v. 14, no. 1, p. 27-37 How to cite?
Journal: Engineering applications of computational fluid mechanics 
Abstract: 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.
URI: http://hdl.handle.net/10397/81731
ISSN: 1994-2060
EISSN: 1997-003X
DOI: 10.1080/19942060.2019.1679668
Rights: © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use,distribution, and reproduction in any medium, provided the original work is properly cited.
The following publication Abdolhossein Hemmati-Sarapardeh, Sassan Hajirezaie, MohamadReza Soltanian, Amir Mosavi, Narjes Nabipour, Shahaboddin Shamshirband & Kwok-WingChau (2020) Modeling natural gas compressibility factor using a hybrid group method of datahandling, Engineering Applications of Computational Fluid Mechanics, 14:1, 27-37 is available at https://dx.doi.org/10.1080/19942060.2019.1679668
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