Abstract
This paper concerns the analysis and simulation of multiphase field data from a deep-water flowline-riser hydrocarbon production system. The system consists of a lazy wave riser leading to the water surface. A major concern associated with lazy wave risers is that liquid slugs and waves can cause significant weight fluctuations that induce variations in the strain on the pipe. In the long term, this can potentially lead to mechanical fatigue that can ultimately compromise the integrity and safety of the system. A prerequisite for predicting the durability of the system is the ability to predict the multiphase flow characteristics inside the pipe, with particular emphasis on slugs and waves. The objective of this work is to explore a method for predicting the flow characteristics of this system for different conditions.
A comprehensive field trial was conducted on this system by varying the production rate in discrete steps, each step lasting at least 12 hours to ensure fully developed flow and converged flow statistics. The riser was equipped with two gamma densitometers that measured the mixture density at two different locations. The primary purpose of these instruments was to validate flow simulation results, which could then subsequently be used with confidence for fatigue calculations.
To simulate the field data, a commercial multiphase flow simulator was applied, using a flow modelling approach called "Slug Capturing". The simulations were initially unsuccessful in reproducing the flow characteristics shown by the gamma densitometers, predicting too much slug flow and too little gas in the slugs. To investigate this matter, a crude oil sample from the field was analyzed in a stir tank setup. The stir tank experiments showed that the crude oil's ability to entrain and separate bubbles was completely different from refined oils with similar thermodynamic properties, and the observed differences were attributed to the presence of surfactants in the crude oil that stabilize gas bubbles.
To account for the observed effects, the closure laws in the simulator pertaining to gas bubble entrainment were tuned to match the field observations. Through this tuning, a good agreement between the simulations and field data was achieved. Specifically, the transition between bubbly flow and slug flow was reproduced accurately, and a good match was obtained for the slug flow characteristics. A key takeaway from this study is that natural surfactants can significantly affect the gas/liquid interaction in multiphase flows, and in such cases, multiphase flow simulators require additional model input or tuning to predict the associated flow behavior.