Prediction and Benchmarking of a Nearly Horizontal Flowline Slug Flow

Abstract In recent years the oil and gas industry has increased its attention to slugging flow-induced vibration challenges due to their effect in deep and shallow water assets operations. Risers, subsea pipelines and jumpers are checked to ensure that the predicted slugging events based on the well’s production life do not consume excessive fatigue capacity and provide a suitable design basis. For shallow water gas production wells, the fatigue generated due to slug events can be a governing case for pipeline and riser design. Due to the complexity of the internal-flow physics, numerical simulations are typically employed to predict the number of expected slug events and characteristics during the design phase. One well-known limitation in commercial flow simulation packages is the prediction uncertainty for slug flows in risers and pipelines. The abrupt changes in the pipeline content density and asset configuration can promote the generation of slugs, increasing the probability of underpredicting the number of events through the asset service life and reducing the accuracy of the slug characteristics prediction. Furthermore, there is no standardized methodology for the slug analysis required in the industry or regulatory agencies. This study documents the current limitations of the industry practices and state-of-the-art methods to predict slug flow that can affect operations and integrity of assets. The first industry flow-induced vibration experiments that couples the internal flow with its structural response are presented. The experimental data collected in this study on slugging characteristics are benchmarked against predictions from flow simulators to address the modeling uncertainties of slug characteristics. The benchmarking study further explains the multiphase model limitations and prediction bias for the slugging phenomenon in a pipeline.