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Integration of Uncertainty Analysis and History Matching: Application in a Complex Case

机译:不确定性分析和历史匹配的整合:在复杂案例中的应用

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The large amount of uncertainties on reservoir modeling increases petroleum production forecast risks. Therefore, the history matching, which refines the simulation model to closely reproduce production data, is a vital procedure once it approximates numerical models to reality providing reliable predictions. As history matching is an inverse problem, the use of multiple models with good match is important to guarantee future analysis. Many methodologies were developed to integrate uncertainty analysis and history matching, in order to mitigate the reservoir uncertainties by using the observed data. In this context, the present article aims to evaluate the application of existing methods on a synthetic complex model (i.e. similar to a real field) and propose new methods with some improvements to be applied in real cases of the petroleum industry. The main characteristic of these methods is the use of differences between observed and simulated data to recalculate the probabilities distribution of uncertain parameters with the purpose of reducing reservoir uncertainties. The redistribution of occurrence probabilities is made with different formulas, representing the distinct four methods discussed: the first two are reviewed from literature and other two proposed by authors. The first proposed method combines the best practices of the two reviewed ones, making it robust to be used in real cases with a great number of wells and production functions to be adjusted such as water production and pressure. The second proposed method is only an iterative application of the first one with a redefinition of attribute values in order to refine the results. A comparison of the results of the four methods shows an evolution in the uncertainty reduction. Besides that, there is a decrease in the dispersion of the representative curves, which are centralized around the history data. Finally, this work presents a simple and practical way of integrating uncertainty analysis with history matching that provides reliable reservoir simulation models for production forecast and risk analysis of future projects.
机译:大量关于储层建模增加石油产量的预测风险不确定性。因此,历史匹配,其提炼的仿真模型,密切重现生产数据,是一个重要的过程,一旦接近数值模型,现实中提供可靠的预测。由于历史匹配是一个反问题,采用多种模型具有良好的匹配是保证未来的分析非常重要。许多方法被开发整合的不确定性分析和历史拟合,为了利用观测数据,以减轻水库的不确定性。在此背景下,本制品旨在评估的现有方法在合成的复合物模型应用(即类似于一个真实的字段),并提出了一些改进的新方法,以在石油工业中的实际情况下被应用。这些方法的主要特征是利用观察到的和仿真的数据之间的差异来重新计算不确定参数的概率分布减小容器的不确定性的目的。出现概率的再分配与不同的配方制成,代表所讨论的不同的四种方法:前两个是从文献回顾和提出了通过作者另外两个。第一个提出的方法结合了这两种审查者的最佳实践,使之成为强大的现实情况下使用与井和生产函数的大量进行调整,比如水的生产和压力。第二种提议的方法是仅在第一个与属性值,以优化结果的重新定义的迭代应用。这四种方法的结果的比较示出了在减少不确定性的演进。除此之外,还有为代表的曲线,这是周围的历史数据集中的分散性下降。最后,这项工作提出了整合与历史匹配,提供可靠的油藏数值模拟模型,产量预测和未来项目的风险分析,不确定性分析的简单实用的方法。

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