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An Autonomic Reservoir Framework for the Stochastic Optimization of Well Placement

机译:井网随机优化的自主储层框架

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The adequate location of wells in oil and environmental applications has a significant economic impact on reservoir management. However, the determination of optimal well locations is both challenging and computationally expensive. The overall goal of this research is to use the emerging Grid infrastructure to realize an autonomic self-optimizing reservoir framework. In this paper, we present a policy-driven peer-to-peer Grid middleware substrate to enable the use of the Simultaneous Perturbation Stochastic Approximation (SPSA) optimization algorithm, coupled with the Integrated Parallel Accurate Reservoir Simulator (IPARS) and an economic model to find the optimal solution for the well placement problem.
机译:井在石油和环境应用中的适当位置对储层管理具有重大的经济影响。然而,确定最佳井位置既具有挑战性,又在计算上昂贵。这项研究的总体目标是使用新兴的Grid基础设施来实现自主的自我优化储层框架。在本文中,我们提出了一种策略驱动的点对点网格中间件支持,以允许使用同时扰动随机近似(SPSA)优化算法,以及集成的并行精确储层模拟器(IPARS)和经济模型来实现找到解决井位问题的最佳方案。

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