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Analysis of the performance of ensemble-based assimilation of production and seismic data

机译：基于集成的生产和地震数据同化性能分析

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Ensemble-based methods have gained popularity as reservoir history-matching techniques. The advantages typically attributed to these methods include the possibility of adjusting a large number of model parameters at a reasonable computational cost, the generation of several alternative models conditioned to data and the ease of implementation. In fact, it is straightforward to adapt these methods to handle different types of data and model variables. Moreover, they are easily coupled with commercial reservoir simulators. Among these methods, the ensemble Kalman filter (EnKF) is by far the most investigated. Iterative forms of the ensemble smoother (ES), on the other hand, are less widespread in the literature. However, ensemble smoothers are much better suited to practical history-matching applications, because they do not require updating dynamical (state) variables and consequently avoid the frequent simulation restarts required by EnKF. This paper presents the results of an investigation on the performance of a variant of ES, namely, ensemble smoother with multiple data assimilation (ES-MDA), to history match production and seismic data of a real field. The paper discusses the quality of the data matches, the plausibility of the history matched models, the ability of the posterior ensemble to assess the uncertainty in the forecasted water production, the effect of the number of iterations and localization. The paper also includes two appendix sections. The first one presents two alternative implementations of the ES-MDA method. The second appendix presents the matrix operations for an efficient implementation of the analysis. (C) 2016 Elsevier B.V. All rights reserved.
机译：基于集合的方法已成为油藏历史匹配技术的流行。这些方法通常具有的优势包括：可以以合理的计算成本来调整大量模型参数，生成适应数据的多个替代模型以及易于实现的优点。实际上，直接调整这些方法来处理不同类型的数据和模型变量很简单。此外，它们很容易与商用油藏模拟器结合使用。在这些方法中，集成卡尔曼滤波器（EnKF）是迄今为止研究最多的方法。另一方面，合奏平滑器（ES）的迭代形式在文献中不那么广泛。但是，集成平滑器更适合于实际的历史记录匹配应用程序，因为它们不需要更新动态（状态）变量，因此避免了EnKF要求频繁的仿真重启。本文介绍了对ES变体（即具有多个数据同化的集成平滑器（ES-MDA））的性能进行研究的结果，以对历史现场的生产和地震数据进行历史匹配。本文讨论了数据匹配的质量，历史匹配模型的合理性，后集合评估预测的产水量不确定性的能力，迭代次数和本地化的影响。本文还包括两个附录部分。第一个介绍了ES-MDA方法的两种替代实现。第二个附录介绍了有效执行分析的矩阵运算。 （C）2016 Elsevier B.V.保留所有权利。

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