(60h) Modelling Salts Effect on Hydrate Inhibition with CPA-Electrolyte and Pseudo-Salt Approach with Excess Gibbs Energy Mixing Rules

Gas hydrate formation analysis and management have become an essential part of engineering work for the correct design, commissioning and operation of offshore and onshore production and transportation.

The conventional engineering approach for suppression of hydrates formation is to add inhibitors such as methanol or glycol to alter the thermodynamic equilibrium so that hydrates cannot form under production conditions. Although there has been much work recently on low-dosage kinetic inhibitors, there are many situations where it remains essential to use thermodynamic inhibitors. In order to accurately predict the hydrate phase behaviour and the dosage of hydrate inhibitors, the equation of state used has to be able to model systems where hydrocarbons, water and other polar components such as methanol are involved, as well as be able take into account of the presence of salts, and their effect on the solubility of water and hydrate inhibitors, and the accumulated hydrate inhibition.

Traditionally cubic equations of state, such as Peng–Robinson (PR) or Redlich–Kwong–Soave (RKS), with simple mixing rules, are not able to predict correct phase behaviour of highly polar mixtures like water and salts. In order to model not only gas and oil phase but must also an aqueous phase with mixed solvents of alcohols, glycols and salts, either complex mixing rules based on Excess Gibbs energy or additional association terms are needed to provide reliable prediction on complex phase equilibria between the fluid and solid phases. In this study two well established models; CPA (Cubic-Plus-Association) with Electrolyte and the advanced version of RKS with NRTL type mixing rule are applied to model the effect of salts and the mixed-solvent electrolytes involving methanol, MEG, DEG and TEG on gas hydrate inhibition.

The study will compare the performance and predictability of the two well-developed models, addresses the importance of accurate fluid model for prediction of hydrate formation and highlight the best practice on modelling the accumulated effect of salts on hydrate inhibition.