Objective During the later stages of gas field exploitation, liquid production from gas wells increases, leading to higher liquid holdup of the flowing medium in the pipeline. This causes many issues such as local liquid loading and seasonal freezing blockage, making significant impact on gas field production and safety. Investigating fluid flow dynamics in gas gathering pipelines and predicting liquid loading are crucial for ensuring safe operations and enhancing gas gathering efficiency.

Methods By integrating production data from a gas field with multiphase flow theory, hydraulic and thermodynamic calculation models were developed for gas gathering pipelines. A simulation algorithm was then proposed to analyze flow conditions, including fluid patterns, liquid holdup, pressure, and temperature at any cross-section of the pipeline. This was achieved through steps such as pipeline feature identification and discretization, flow parameter initialization, and physical property database calling. The accuracy of the flow simulation algorithm for gas gathering pipelines was verified by comparing the calculation results of pressure difference at both ends of several gas gathering pipelines in this gas field with results from the mainstream commercial software OLGA and the corresponding field measurement data. Finally, the simulation algorithm was employed to predict liquid loading in a gas gathering pipeline of this gas field.

Results The mean relative error (MRE) of the pressure difference calculated by this algorithm was 0.101, compared to 0.267 for OLGA software. The results obtained from this algorithm were closer to the field measurements than those from OLGA. Building on this, the flow pattern, pressure, and liquid holdup in the gas gathering pipeline were analyzed with varied conditions of mixture’s mass flow rate, moisture content, and outlet temperature, etc. This algorithm was utilized to predict liquid loading in the gas gathering pipeline segment between Stations 5^# and 6^#. The maximum liquid holdup was 0.37, indicating a significant issue with liquid loading that necessitated appropriate measures to prevent hazardous working conditions.

Conclusion This algorithm has practical significance for analyzing flow characteristics and predicting liquid loading in gas gathering pipelines. Engineering technicians in gas field enterprises can utilize this algorithm for on-site process simulation calculations, enabling them to develop effective plans for liquid loading treatment and mitigate hazardous working conditions. This algorithm represents a valuable effort to challenge the monopoly of foreign commercial software. The next step should involve debugging and validating it in other gas field blocks to enhance its versatility and stability.