大斜度井气举优化计算流体动力学

F. Sajjad, S. Chandra, A. Wirawan, Silvya Dewi Rahmawati, Michelle Santoso, Wingky Suganda
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引用次数: 0

摘要

在气举实施过程中,了解大斜度井的流动特性对于避免因液体回降和堵塞而造成的生产损失至关重要,即使在高产油藏中也是如此。在这项工作中,我们利用计算流体动力学(CFD)来优化大斜度井中不同流动特性下的气举设计。该分析结果直接应用于Arjuna海上油田实例。Arjuna海上油田拥有气举井,产自高渗透油藏。然而,由于井斜的影响,有几口井遭受了巨大的产量损失。在斜度井中,频繁的回液会造成堵塞,从而降低产量。基于此,我们采用CFD框架进行气举优化。首先采用气举井的几何形状作为模拟的计算域。采用基于图像的网格技术捕捉井眼轨迹和内部几何形状。其次,利用可压缩Navier-Stokes方程和有限体积法对流动特性进行了评价。我们捕捉液体回退和液体积聚在肘部的位置,以估计生产损失。我们考虑了粘度、密度、气举阀位置、注入气量和储层压力的变化。最后以生产损失为目标函数进行梯度优化,得到最优设计。最后的结果被用来优化当前的设计。仿真结果表明,产能指标、管径和井斜对产量损失有较大影响。在大管径、大井斜时,重力控制流体的流动。因此,鼻涕虫在肘部发育和积累。这种积聚阻碍了气体流动,降低了产量。改变注气速率会影响举升密度。高注入速度会导致液气分离,而低注入速度不会降低液体密度。气举阀位置的改变会影响液气混合。这也决定了注气的成本。因此,我们需要同时优化这两个参数。Arjuna油田30口井中有6口出现严重的回液现象,导致产量显著下降。模拟结果表明,管道内径覆盖了40%,阻碍了气体的流动。我们通过改变气举阀的位置和调整注气量来进行优化。通过将研究结果应用于现场案例,我们成功地将产量提高了20%。我们提供了一种将高分辨率模拟与现场设计相结合的有效方法,并改变了目前气举完井设计的概念。该模拟使工程师能够更深入地了解大斜度井的流动保障情况。
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Computational Fluid Dynamics for Gas Lift Optimization in Highly Deviated Wells
In the implementation of gas lift, understanding flow behavior in highly-deviated well is critical in avoiding production loss due to liquid fallback and blockage, even in highly-productive reservoir. In this work, we utilize Computational Fluid Dynamics (CFD) to optimize gas lift design under various flow behavior in highly-deviated well. The analysis is directly implemented into Arjuna offshore field case. Arjuna offshore field has gas-lifted wells, producing from a high-permeability reservoir. However, several wells suffer from huge production loss due to the effect of well's deviation. In deviated well, there exists frequent liquid fallback causes blockage, therefore, reducing the production. Motivated by this issue, we use CFD framework to perform gas lift optimization. We firstly adopt the geometry of gas-lifted wells as the computational domains for our simulation. An image-based meshing technique is deployed to capture the well's trajectory and internal geometry. We secondly utilize compressible Navier-Stokes equation and Finite Volume Method to evaluate the flow behavior. We capture the location of liquid fallback and liquid accumulation at elbows to estimate production loss. We consider the variation of viscosity, density, gas lift valve placement, injected gas rate, and reservoir pressure. We finally perform gradient-based optimization utilizing production loss as the objective function to obtain optimum design. The final result is then used to optimize the current design. The simulation results show that productivity index, pipe diameter, and deviation heavily influence the amount of production loss. At big pipe diameter and high deviation, the gravitational force governs the fluid flow. Therefore, slugs are developed and accumulated at elbows. This accumulation blocks gas flow and reduces production. Changing the gas injection rate affects the lifted density. High injection rate triggers segregation between the liquid and gas, while low injection rate does not reduce the liquid density. Shifting the gas lift valve placement influence the mixing between the liquid and gas. It also determines the cost of gas injection. Hence, we need to optimize both parameters at once. Six of thirty wells in Arjuna field experience severe liquid fallback, therefore, the production significantly decreases. The simulation shows up to 40% coverage of the pipe internal diameter, which blocks the gas flow. We perform the optimization by shifting the gas lift valve placement and adjusting the gas injection rate. By implementing the study result into the field case, we manage to improve the production by 20%. We provide an effective way to connect high-resolution simulation to the field design and revise the current concept in designing gas lift well completion. The simulation allows engineers to provide more insight on flow assurance in highly deviated wells.
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