Modeling viscosity of methane, nitrogen, and hydrocarbon gas mixtures at ultra-high pressures and temperatures using group method of data handling and gene expression programming techniques

Farzaneh Rezaei; Saeed Jafari; Abdolhossein Hemmati-Sarapardeh; Amir H. Mohammadi

Your Location：

Home >

Browse articles >

Modeling viscosity of methane, nitrogen, and hydrocarbon gas mixtures at ultra-high pressures and temperatures using group method of data handling and gene expression programming techniques

Energy, Resources and Environmental Technology | Updated：2026-01-06

- Modeling viscosity of methane, nitrogen, and hydrocarbon gas mixtures at ultra-high pressures and temperatures using group method of data handling and gene expression programming techniques
- Modeling viscosity of methane, nitrogen, and hydrocarbon gas mixtures at ultra-high pressures and temperatures using group method of data handling and gene expression programming techniques
- 中国化学工程学报（英文版） 2021年32卷第4期页码：431-445
- Affiliations：
  
  1. Department of Petroleum Engineering, Shahid Bahonar University of Kerman, Kerman,Iran
  2. Institute of Research and Development, Duy Tan University, Da Nang,Vietnam,550000
  3. Faculty of Environment and Chemical Engineering, Duy Tan University, Da Nang,Vietnam,550000
  4. Institut de Recherche en Génie Chimique et Pétrolier(IRGCP), Paris Cedex,France
  5. Discipline of Chemical Engineering, School of Engineering, University of KwaZulu-Natal, Howard College Campus, King George V Avenue, Durban 4041, South Africa
- Author bio：
- Funds：
- DOI：
  中图分类号：
- 纸质出版：2021
- Accepted：
Scan QR Code
Farzaneh Rezaei, Saeed Jafari, Abdolhossein Hemmati-Sarapardeh, 等. Modeling viscosity of methane, nitrogen, and hydrocarbon gas mixtures at ultra-high pressures and temperatures using group method of data handling and gene expression programming techniques[J]. 中国化学工程学报（英文版）, 2021,32(4):431-445.

Farzaneh Rezaei, Saeed Jafari, Abdolhossein Hemmati-Sarapardeh, Amir H. Mohammadi. Modeling viscosity of methane, nitrogen, and hydrocarbon gas mixtures at ultra-high pressures and temperatures using group method of data handling and gene expression programming techniques[J]. Chinese Journal of Chemical Engineering, 2021, 32(4): 431-445.
Farzaneh Rezaei, Saeed Jafari, Abdolhossein Hemmati-Sarapardeh, 等. Modeling viscosity of methane, nitrogen, and hydrocarbon gas mixtures at ultra-high pressures and temperatures using group method of data handling and gene expression programming techniques[J]. 中国化学工程学报（英文版）, 2021,32(4):431-445. DOI：

Farzaneh Rezaei, Saeed Jafari, Abdolhossein Hemmati-Sarapardeh, Amir H. Mohammadi. Modeling viscosity of methane, nitrogen, and hydrocarbon gas mixtures at ultra-high pressures and temperatures using group method of data handling and gene expression programming techniques[J]. Chinese Journal of Chemical Engineering, 2021, 32(4): 431-445. DOI：

摘要

Abstract

Accurate gas viscosity determination is an important issue in the oil and gas industries. Experimental approaches for gas viscosity measurement are time-consuming

expensive and hardly possible at high pressures and high temperatures (HPHT). In this study

a number of correlations were developed to estimate gas viscosity by the use of group method of data handling (GMDH)-type neural network and gene expression programming (GEP) techniques using a large data set containing more than 3000 experimental data points for methane

nitrogen

and hydrocarbon gas mixtures. It is worth mentioning that unlike many of viscosity correlations

the proposed ones in this study could compute gas viscosity at pressures ranging between 34 and 172 MPa and temperatures between 310 and 1300 K. Also

a comparison was performed between the results of these established models and the results of ten well-known models reported in the literature. Average absolute relative errors of GMDH models were obtained 4.23%

0.64%

and 0.61% for hydrocarbon gas mixtures

methane

and nitrogen

respectively. In addition

graphical analyses indicate that the GMDH can predict gas viscosity with higher accuracy than GEP at HPHT conditions. Also

using leverage technique

valid

suspected and outlier data points were determined. Finally

trends of gas viscosity models at different conditions were evaluated.

关键词

Keywords

references

浏览量

Downloads

CSCD

文章被引用时，请邮件提醒。

Submit

工具集

关联资源

A durable fluorine-free polyurethane-coated fabric with switchable super-wetting properties under mild pH conditions for controllable oil/water separation

Understanding temperature-dependent degradation in proton exchange membrane water electrolyzer: The critical role of porous transport layer

Non-phosgene synthesis processes of isocyanates: One-step and two-step routes

Synergistic Ba/Na promotion of BaFe2O4-derived catalysts for enhanced CO2 hydrogenation to light olefins

Revealing critical factors in lignite-water interactions: From atomic to macroscopic