This work presents the effect of hydrogen sulfide gas on the phase behavior of both methane gas hydrate formation and CO 2 gas hydrate formation. For this, the thermodynamic equilibrium conditions for various gas mixtures containing CH 4 /H 2 S and CO 2 / H 2 S are initially found by simulation using PVTSim software. These simulated results are compared using an experimental approach and the available literature. Then, the thermodynamic equilibrium conditions generated by simulation are used for generating Hydrate Liquid−Vapor-Equilibrium (HLVE) curves to understand the phase behavior of gases. Further, the effect of hydrogen sulfide on the thermodynamic stability of methane and carbon dioxide hydrates was studied. It was clearly observed from the results that an increase in H 2 S composition in the gas mixture decreases the stability of CH 4 and CO 2 hydrates.

In this work, an experimental investigation has been carried out to understand the Kinetic behavior of gas hydrates formation in a multiphase gas dominant pipeline system. The multiphase system consists of Crude oil, Natural Gas system with high Carbon dioxide and deionized water. Experiments are conducted using the Raman Gas hydrate reactor with the operating conditions in line with the real time conditions. The Induction time was calculated for all the experiments and the kinetic behavior was evaluated. Also, a statistical regression model has been developed to predict the induction time. Also, this model is used for evaluating the most influential parameters on induction time prediction. It was found that the Induction time plays a major role in the kinetics of gas hydrates. The observations suggested that the higher the induction, the gas hydrates formation initiation is delayed. Keywords: Multiphase Pipelines, Gas Hydrates, Kinetic Behavior, Statistical Regression Analysis.

Experimental PTx data have been measured and reported for three binary mixtures containing morpholine under 18 conditions using a Sweitoslawski-type ebulliometer. The measured pressure (P), temperature (T), and liquid­(x) composition (PTx) data were correlated by five popular excess free-energy models using the Gauss–Newton (GN) optimization algorithm to obtain the vapor composition and optimized parameters simultaneously. In general, the Margules model had been found to be the best in vapor composition predictions. UNIFAC predictions for the activity coefficients and vapor compositions were also made for each dataset to evaluate the suitability of group interaction parameters published for two UNIFAC versions. However, the results were not compatible with the predictions by the two-parameter models. The binary mixtures studied in the present work exhibited negative deviations from Raoult’s law with a few exceptions. A comparison made between the measured vapor pressure data and the available literature data for four pure components showed good agreement. When the Tx data of methanol–morpholine mixture at 74.26 and 101.32 kPa were compared with the published data, large deviations were observed for the data at 101.32 kPa. Moreover, the pair of activity coefficients at infinite dilution data for each binary system were predicted using Margules and UNIFC models.