基于改进间歇泉算法的高倾角油藏气水双向驱自动优化

Optimized Bidirectional Gas–water Displacement in High-inclination Reservoirs Using an Improved Geyser-inspired Algorithm

  • 摘要: 构建矿场尺度高倾角井组模型,提出融合 Halton 序列初始化、切线飞行策略与正余弦扰动机制的改进间歇泉优化算法(IGEA),以优化注采速度、周期与转注时机等关键参数。IGEA在收敛速度、优化精度与稳定性方面均优于遗传算法(GA)与粒子群优化算法(PSO),平均净现值分别提高了1%和6%。不同注入方式对开发效果影响显著:水气交替注入在净现值与采收率方面表现最优,连续注气次之,间歇注气效果较弱。目标函数选择亦影响优化结果:净现值导向策略有助于提升早期产能与资本回收,产量导向策略则更强调注采平衡和最终采收率。

     

    Abstract: A field-scale high-inclination well pattern model is constructed, and an improved Geyser-inspired optimization algorithm (IGEA) is proposed by integrating Halton sequence initialization, tangent flight strategy, and sine–cosine perturbation mechanism to optimize key parameters such as injection/production rates, cycles, and switching timing. Results show that IGEA outperforms GEA and PSO in terms of convergence speed, optimization accuracy, and stability, with average net present value improved by 1% and 6%, respectively. Further analysis indicates that different injection strategies have a significant impact on development performance: water-alternating-gas injection performs best in terms of both net present value and oil recovery, followed by continuous gas injection, while intermittent gas injection is less effective. The choice of objective function also affects optimization results: NPV-oriented strategies help to improve early production and capital recovery, whereas production-oriented strategies place greater emphasis on maintaining injection–production balance and maximizing ultimate recovery. This study provides an effective optimization approach for the development of high-inclination reservoirs.

     

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