Hydrate temperature depression of MEG solutions at concentrations up to 60 wt%: Experimental data and simulation results

P V Hemmingsen, Rhoderick William Burgass, K S Pedersen, K Kinnari, H Sorensen

    Research output: Contribution to journalArticle

    19 Citations (Scopus)
    38 Downloads (Pure)

    Abstract

    Literature data for the hydrate temperature depression by mono-ethylene glycol (MEG) show some scattering and no thermodynamic model has been able to match all of the available data found in the open literature. This paper presents hydrate equilibrium data for a mixture of 88.13 mol% methane and 11.87 mol% propane with MEG added to the water phase in concentrations from 0 to 60 wt%. That particular hydrocarbon mixture was chosen because it with pure water at pressures above 60 bar shows hydrate dissociation temperatures above 20 °C and because hydrate dissociation temperatures above the freezing point of water are still seen when the aqueous phase contains 50 wt% MEG. This range of inhibitor dosage is typical in North Sea pipelines, and for optimal hydrate control it is vital to have high quality experimental data of hydrate equilibrium. Previously published data for the same hydrocarbon mixture as used in this study show a lower hydrate depression by MEG compared to other available data. The new data from this work show that MEG is more efficient as a hydrate inhibitor than the previously published data for the same system has suggested. The new data and earlier MEG inhibition data for other systems can all be modeled within experimental uncertainty using the hydrate model of Munck et al. and a conventional cubic equation of state for the H2O–MEG component pair.
    Original languageEnglish
    Pages (from-to)175-179
    Number of pages5
    JournalFluid Phase Equilibria
    Volume307
    Issue number2
    DOIs
    Publication statusPublished - Aug 2011

    Fingerprint Dive into the research topics of 'Hydrate temperature depression of MEG solutions at concentrations up to 60 wt%: Experimental data and simulation results'. Together they form a unique fingerprint.

    Cite this