多尺度流动模拟在油藏工程实践中的应用

Sanjoy Kumar Khataniar, Daniel de Brito Dias, Rong Xu
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引用次数: 6

摘要

将一种新的多尺度序列全隐式(MS SFI)油藏模拟方法应用于一组油藏工程问题,以了解其实用性。进行评估,以突出该方法在性能方面带来实质性优势的领域,并解决现有方法未能成功解决的问题。这项工作首次在商业油藏模拟器中实现了多尺度顺序全隐式方法。简要讨论了该方法的主要特点及其实现。在大约40个真实世界模型的现场测试和商业化过程中获得的知识通过在公共领域中提供的更简单但具有代表性的数据集来说明。采用主力鲁棒全隐式(FI)方法作为基准测试的参考。MS SFI方法能忠实地再现黑油问题的FI结果。结果表明,MS - SFI方法在地下不确定性量化、代表性模型选择、模型标定和优化等方面具有较好的油藏工程决策支持能力。MS SFI方法在处理严重的储层非均质性方面显示出巨大的潜力。当将EOR过程从实验室扩展到现场时,通常会忽略包括精细尺度异质性的挑战,而MS SFI和高性能计算(HPC)的结合似乎已经找到了一个实用的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Aspects of Multiscale Flow Simulation with Potential to Enhance Reservoir Engineering Practice
A new implementation of a multiscale sequential fully implicit (MS SFI) reservoir simulation method is applied to a set of reservoir engineering problems to understand its utility. An assessment is made to highlight areas where the approach brings substantial advantage in performance as well as address problems not successfully resolved by existing methods. This work makes use of the first ever implementation of the multiscale sequential fully implicit method in a commercial reservoir simulator. The key features of the method and implementation are briefly discussed. The learnings gained during field testing and commercialization on about forty real world models is illustrated through simpler, but representative data sets, available in the public domain. The workhorse robust fully implicit (FI) method is used as a reference for benchmarking. The MS SFI method can faithfully reproduce FI results for black oil problems. We conclude that the MS SFI method has the capability to support reservoir engineering decision making especially in the areas of subsurface uncertainty quantification, representative model selection, model calibration and optimization. The MS SFI method shows immense potential for handling prominent levels of reservoir heterogeneity. The challenge of including fine-scale heterogeneity, which is often overlooked, when scaling up EOR processes from laboratory to field, appears to have found a practical solution with a combination of MS SFI and high-performance computing (HPC).
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