Hydrodynamic slug flow is the prevailing flow regime in oil production, yet industry still lacks a comprehensive model, based on first principles, which fully describes hydrodynamic slug flow. This paper describes a very simple, time-dependent, two-phase (gas-liquid) model which is capable of producing hydrodynamic slugging from first principles.
The new method can be applied for evaluation of slugging potential for oil pipelines. The model is capable of producing slug lengths and frequencies, as well as slug hold-ups. The model has been compared to the published Prudhoe Bay field data gathered by Brill et al. The model has been able to predict the transition from homogeneous to slug flow, and also give information about slug lengths and frequencies.
Such a simple model could be a very excellent jumping off point for building more complex models capable of predicting slug distributions from first principles, without any need for additional user input. No such model currently exists.
While hydrodynamic slug flow is an inherently transient phenomenon, it has historically been modeled as a ‘pseudo steady-state’ which ignores the fundamentally transient nature of the flow. Even in instances where the individual slugs are introduced and tracked in a Lagrangian frame (so-called ‘slug tracking’)1, the results have been somewhat disappointing, in that the ultimate slug distributions are heavily influenced by user input. This paper examines another approach - where the fundamental transient nature of hydrodynamic slug flow is accounted for in the model.
In order to formulate a model for slug flow, we must first develop a ‘point model’ for an individual pipeline segment, or computational cell, in a pipeline. This pipeline segment must then be joined with other pipeline segments upstream and downstream of it to form a ‘steady-state’ model for the pipeline. Lastly, these steady-state solutions must be implemented into a transient scheme; a proper model of hydrodynamic slug flow absolutely requires that slugging not be treated as a pseudo-steady-state, but as an inherently transient phenonenon.