Modeling of hydrate formation prediction in binary components of natural gas

Aijaz Abbasi, Fakhruldin Mohd Hashim, Affiani Machmudah

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Temperature is calculated as a function of gas gravity and pressure using an exponential function with two constant parameters, a and b. To obtain the best prediction model of gas hydrate formation, the behavior of these parameters in response to changes in gas gravity is monitored. Methane-ethane, methane-propane, ethane-propane, and ethane-carbon dioxide are among the binary components to which the suggested model is applied. The suggested predictive model outperforms the existing correlation approaches, such as Hammerschmidt, Motiee, and Ghiasi correlations, according to statistical analysis. The type of gases that make up the hydrate has a big impact on the gas hydrate equilibrium line, and the predictive model's constant values are different for each binary component. As a result, this study indicates that rather than constructing an empirical correlation-based on the assumption that the specific gas gravity is a general characteristic independent of the kind of gas hydrate mixture, a predictive model should be established for each gas hydrate mixture.

Original languageEnglish
Pages (from-to)2025-2037
Number of pages13
JournalPetroleum Science and Technology
Volume40
Issue number16
DOIs
Publication statusPublished - 2022

Keywords

  • Binary components
  • clean energy
  • gray wolf optimizer
  • hydrate formation
  • predictive analytics
  • thermodynamic

Fingerprint

Dive into the research topics of 'Modeling of hydrate formation prediction in binary components of natural gas'. Together they form a unique fingerprint.

Cite this