## 1 Introduction
OLGA can simulate diverse fluid behaviors, including single-phase, multi-phase flow, and sediment transport. Moreover, OLGA features fast computation and precise forecasting of complex flows, dynamic changes, and transient responses inside the pipeline. [PERSON] et al. [40] used OLGA software to simulate experiments and predict vibration caused by slug flow in risers and subsea pipelines. OLGA and experimental data were compared using OrcaFlex for vibration analysis, revealing differences in bubble density and flow field. [PERSON] et al. [41] evaluated corrosion inhibition severity by random forest (RF) predicting maximum slug lengths (MSL) with OLGA pipeline simulation and shale gas field well geometry. The MSL was projected onto a 3D map as the output of RF and had satisfactory results in trained RF. [PERSON] et al. [42] used OLGA7.0 to study gas-liquid flow regimes in hilly terrain pipelines, identifying four regimes. OLGA7.0 accurately predicted severe slugging and stable flow but had poor accuracy for dual-peak slug and oscillating flow with insufficient sensitivity to gas changes. [PERSON] and [PERSON] [43] utilized an OLGA simulator to predict the flow regimes in vertical pipes of 35 oil wells, and the results showed good consistency between the predicted and measured oil flow rates. The impact of flow regime changes on accuracy was minimal, and the possible variations between oil rate measurements were emphasized. [PERSON] et al. [44] tested pipeline leak detection with OLGA software, and leaks ranging from 0-50%. Large leaks caused the pressure/mass flow rate to decrease, while temperature initially dropped and rose after 25%. OLGA has extensive applications in long-distance and storage pipelines, exhibiting efficacy in flow regime identification, slug flow characteristics analysis, pipeline corrosion, and leakage detection. The present study aims to model and analyze the dynamic process of slug flow formation in pipelines by combining experiments and OLGA software. Initially, high-speed camera experiments are performed to observe slug flow formations under various liquid accumulation volumes and incline angles. Then, an OLGA model is constructed to confirm the observed flow regime, pressure, and velocity. Finally, the formation stages of slug flow are investigated, and the sensitivity of slug flow to pressure fluctuations is analyzed. The contribution of the article is summarized as follows. Firstly, an experimental setup is established to simulate energy storage gas transmission pipelines, enabling the collection of pipeline pressure data that elucidates the genesis of slug flow. This allows for the categorization of slug flow stages based on pressure dynamics. Subsequently, OLGA software is employed to simulate the energy storage gas transmission pipeline, facilitating an analysis of slug flow formation. A meticulous comparison and scrutiny of flow regimes, pressure variations, and slugging velocities against experimental results are carried out, resulting in a notable alignment between the two. Ultimately, the synergistic integration of the OLGA model and experimental findings effectively elucidate the intricate progression of liquid accumulation in energy storage gas transmission pipelines. This comprehensive approach supplements research into compressed gas energy storage systems, contributing substantively to the field. This paper is structured as follows. Section 2 introduces the test rig and outlines the experimental procedure. Section 3 describes the OLGA model used in this study. Section 4 presents the experimental results and provides a comprehensive analysis of the data obtained from the OLGA simulation. Finally, the conclusions and expectations are provided in Section 5.