Research subject: Gas hydrate formation in natural gas transmission pipelines represents a critical operational challenge in gas processing and transportation systems, as it can lead to a pressure drop, flow restriction, pipeline blockage, a production shutdown, and severe safety hazards. Nevertheless, controlled gas hydrate formation can serve as a novel technology for natural gas storage. In this study, the thermodynamic conditions of hydrate formation and natural gas storage capacity were experimentally and computationally evaluated for the NF Unit of Bandar Imam Petrochemical Complex (BIPC) using natural gas samples collected from transmission pipelines.
Research approach: Several predictive correlations and thermodynamic models, including the Makogon, Towler–Mokhatab, Hammerschmidt, and gas gravity methods, were evaluated and compared against specialized hydrate prediction software, namely Hydrate Plus, CSMGem, Hydrate-Off, and DWHC-HWU. In addition, experiments were performed using the constant-volume method at initial pressures of 16.1–52.2 bar and temperatures of 266.3–279.9 K, establishing hydrate equilibrium conditions at 12.4–49.0 bar and 4.8–16.1 °C (277.95–289.25 K). The gas storage capacity behavior was further modeled using Response Surface Methodology (RSM).
Main results: Experimental and modeling results revealed that the Hydrate-Off and DWHC-HWU software tools exhibited the highest accuracy in predicting hydrate formation conditions for the studied gas composition. Experimental findings demonstrated that the natural gas storage capacity in the hydrate phase varied within the range of 29.88 to 64.58 standard gas volume per volume of hydrate (V/V), with the maximum storage capacity of 64.58 (V/V) obtained at an initial pressure of 52.2 bar and a temperature of 279.9 K. Parametric analysis indicated that increasing the initial pressure substantially enhances the storage capacity by elevating the driving force for gas penetration into hydrate cages, whereas increasing temperature exerts an inhibitory effect on capacity due to reduced gas solubility in the liquid phase and decreased structural stability. Finally, the empirical regression model derived from the Response Surface Methodology (RSM) with a desirable coefficient of determination (R2=98.34) exhibited excellent agreement with experimental data, validating the accuracy of storage capacity predictions under operational conditions.