Investigation of the Solubility of Elemental Sulfur (S) in Sulfur-Containing Natural Gas with Machine Learning Methods

Yuchen Wang, Zhengshan Luo (), Jihao Luo, Yiqiong Gao, Yulei Kong and Qingqing Wang
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Yuchen Wang: School of Management, Xi’an University of Architecture and Technology, Xi’an 710055, China
Zhengshan Luo: School of Management, Xi’an University of Architecture and Technology, Xi’an 710055, China
Jihao Luo: School of Computer Science, Beijing Institute of Technology, Beijing 100081, China
Yiqiong Gao: School of Management, Xi’an University of Architecture and Technology, Xi’an 710055, China
Yulei Kong: School of Management, Xi’an University of Architecture and Technology, Xi’an 710055, China
Qingqing Wang: School of Management, Xi’an University of Architecture and Technology, Xi’an 710055, China

IJERPH, 2023, vol. 20, issue 6, 1-21

Abstract: Some natural gases are toxic because they contain hydrogen sulfide (H 2 S). The solubility pattern of elemental sulfur (S) in toxic natural gas needs to be studied for environmental protection and life safety. Some methods (e.g., experiments) may pose safety risks. Measuring sulfur solubility using a machine learning (ML) method is fast and accurate. Considering the limited experimental data on sulfur solubility, this study used consensus nested cross-validation (cnCV) to obtain more information. The global search capability and learning efficiency of random forest (RF) and weighted least squares support vector machine (WLSSVM) models were enhanced via a whale optimization–genetic algorithm (WOA-GA). Hence, the WOA-GA-RF and WOA-GA-WLSSVM models were developed to accurately predict the solubility of sulfur and reveal its variation pattern. WOA-GA-RF outperformed six other similar models (e.g., RF model) and six other published studies (e.g., the model designed by Roberts et al.). Using the generic positional oligomer importance matrix (gPOIM), this study visualized the contribution of variables affecting sulfur solubility. The results show that temperature, pressure, and H 2 S content all have positive effects on sulfur solubility. Sulfur solubility significantly increases when the H 2 S content exceeds 10%, and other conditions (temperature, pressure) remain the same.

Keywords: sulfur-containing natural gas; sulfur solubility; machine learning; hydrogen sulfide (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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