SMARTDRAIN:集成了流线飞行时间和穷举搜索算法的智能井位优化工作流程

P. Ekkawong, Wich Huengwattanakul, Pichaya Ruthairung, A. Rittirong, S. Vitoonkijvanich, Kasama Itthisawatpan
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引用次数: 2

摘要

在勘探开发业务中,最佳井位既具有很高的挑战性,又非常重要,因为它会影响油田开发决策。通常情况下,井位是根据井距手动进行的,这可能无法有效地捕捉到储层地质的影响,特别是在储层非均质性高的情况下。现代技术通过油藏模拟将井位视为离散优化问题,从而应用启发式算法搜索最佳井位,从而解决了这一问题。然而,这些方法需要大量的计算量,这阻碍了寻找全局最优解的新技术的任何努力。本文提出了一种创新的井位优化工作流程,通过简化飞行时间,最大限度地减少了利用排水量进行模拟的计算时间。在很短的时间内进行油藏模拟,以获得所有拟建井位的流线。沿着流线的飞行时间属性表示理论示踪粒子沿着每条流线移动到生产者(压力吸收)所需的理论时间。然后,利用飞行时间和储层性质计算每个生产商的油气排量。其中,它是表示在给定的生产周期内,有多少油气可以运移到井中的关键参数。该工作流程将在给定井数的情况下寻找最佳井位,以最大限度地提高油气排量。该方法将油藏模拟转化为数值矩阵联合优化,可以以极快的计算速度(单次迭代不到1秒)进行。快速的计算效率使得穷举搜索算法能够评估数百万个可能的井组合,从而保证全局最优解决方案。该工作流程已通过综合2D仿真模型在概念上得到验证,提供了一种类似模式的方案来模仿传统方法。此外,该方法已成功地进行了现场油藏模拟测试。该算法在不增加计算负担的情况下,证明了优化井位优于传统方法的优点。工作流程也被设计为通过MATLAB和MS-Excel进行简单的用户交互实现自动化;也就是SMARTDRAIN包。这允许工程师/地质学家将其作为通用工作流来实现,而不需要广泛的数学算法知识。由于这种计算效率和改进的最优解,该方法可以作为一种新的井位优化标准,在油田开发规划和优化中增加竞争价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SMARTDRAIN: An Intelligent Workflow for Well-Placement Optimisation by Integrating Streamlines Time-of-Flight and Exhaustive Search Algorithm
Optimal well placement remains both highly challenging and significantly important in the E&P business since they impact field development decision making. Conventionally, well placement is performed manually based on well spacing, which may not capture the effect of reservoir geology effectively, especially in cases of high reservoir heterogeneities. Modern techniques tackle this problem by treating well locations as discrete optimisation problems through reservoir simulations, and thus apply heuristic algorithms to search for optimal well locations. However, these methods require considerable computational effort, which forestall any efforts at novel techniques in searching to for global optimal solutions. This paper presents an innovative well placement optimisation workflow to minimize the calculation time of simulation using drainage volume via streamlines time-of-flight. A reservoir simulation is run for a short period of time to acquire streamlines for all proposed well locations. The time-of-flight property, along streamlines, indicates the theoretical time required for a theoretical tracer particle to move along each streamline to a producer (pressure sink). The time-of-flight, together with reservoir properties, are then used to calculate the hydrocarbon drainage volume from each producer. In which, it is the key parameter to suggest that how much hydrocarbon can move to wells with a given production period. This workflow will search for optimal well locations to maximize the hydrocarbon drainage volume with a given number of wells. The approach translates reservoir simulation to numerical matrix union optimisation, which can be carried out at an extremely fast computational speed (less than a second for a single iteration). The expedited calculation efficiency allows exhaustive search algorithms to evaluate millions of possible well combinations and can, consequently, guarantee a global optimal solution. The workflow has been conceptually proven with a synthetic 2D simulation model, providing a pattern-like scheme to mimic the conventional approach. Furthermore, it has been successfully tested with field scale reservoir simulations. The algorithm demonstrates the advantages of optimized well-placement over conventional methods without much of an increased computational burden. The workflow is also designed to be automated with a simple user-interaction via MATLAB and MS-Excel; namely, the SMARTDRAIN package. This allows engineers/geologists to implement it as a generic workflow without requiring extensive knowledge in mathematical algorithms. With such calculation efficiency and improved optimal solution, this approach can be applied as a new well placement optimisation standard that would add competitive value in field development planning and optimisation.
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