Simulation of Multiphase Fluid-Hammer Effects During Well Startup and Shut-in
In this study, well-known commercial software that is capable of modeling fully transient multiphase flow in wellbore and pipeline has been used to characterize the fluid-hammer effects of well shut-in and startup on the coupled subsurface and surface systems. The original work was performed by applying sensitivity analysis to a typical production system, including well completion, wellbore, downhole equipment (e.g., packer), and the associated surface equipment (i.e., flowline, riser, and valves). This study summarizes the general course of key factors that worsen the fluid-hammer effects. Fluid hammer is also known as water hammer, a shock wave produced by the sudden stoppage of, or reduction in, fluid flow.
Field operations, such as pressure-transient analysis, facility maintenance, and workover, require a well shut-in process. For a typical production system, the resultant sudden rises in pressure can be critical because they have a direct impact on equipment (i.e., unsetting of the packer) and may cause damage to instrumentation. This paper provides estimates of the typical ratio of transient shock in pressure and flow rate to preconditional values, and the duration of such pressure shocks. It also proposes the best location for the shut-in valve and the length of flowline needed to reduce the fluid-hammer effects.
This is a pioneering approach to integrate multiphase-flow modeling of transient fluid-hammer effects by targeting flow-assurance issues. The software used in the study is a fully transient, commercial flow-assurance simulator, and it has been used extensively for well-dynamics studies. The selected tool enables the integrated approach [i.e., from sandface (bottomhole) to wellhead and topside platform, accordingly], which can be applied to surface-facility design and can serve as guidance in field operations to avoid hydrocarbon leakages.
Neural Networks Plus CFD Speed Up Simulation of Fluid Flow
High-fidelity 3D engineering simulations are valuable in making decisions, but they can be cost-prohibitive and require significant amounts of time to execute. The integration of deep-learning neural networks with computational fluid dynamics may help accelerate the simulation process.
As Exciting as Watching Scale Grow: Real-Time Observations Generate New Control Ideas
The chemical reactions creating buildups of scale that can clog a well can be replicated in a chemical lab, but researchers are finding many more variables on the surfaces of pipes that need to be considered.
Greedy Pursuit: Algorithms Show Promise in Measuring Multiphase Flow
“Greedy pursuit” in the realm of algorithms is a good thing. Saudi Aramco studied such algorithms to produce images simulating the flow inside a pipe’s cross section, possibly reducing the need for separator-based multiphase flowmeters.
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15 May 2019
14 May 2019