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Automatic History Matching in Petroleum Reservoirs Using the TSVD Method

机译:使用TSVD方法的石油储层自动历史匹配

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History matching is an important inverse problem extensively used to estimate petrophysical properties of an oil reservoir by matching a numerical simulation to the reservoir's history of oil production. In this work, we present a method for the resolution of a history matching problem that aims to estimate the permeability field of a reservoir using the pressure and the flow rate observed in the wells. The reservoir simulation is based on a two-phase incompressible flow model. The method combines the truncated singular value decomposition (TSVD) and the Gauss-Newton algorithms. The number of parameters to estimate depends on how many gridblocks are used to discretize the reservoir. In general, this number is large and the inverse problem is ill-posed. The TSVD method regularizes the problem and decreases considerably the computational effort necessary to solve it. To compute the TSVD we used the Lanczos method combined with numerical implementations of the derivative and of the adjoint formulation of the problem.
机译:历史匹配是一个重要的反问题,广泛用于通过将数值模拟与储层的石油生产历史相匹配来估计储层的岩石物理性质。在这项工作中,我们提出了一种解决历史匹配问题的方法,该方法旨在使用在井中观测到的压力和流速来估算储层的渗透率场。储层模拟基于两相不可压缩流动模型。该方法结合了截断奇异值分解(TSVD)和高斯-牛顿算法。估计参数的数量取决于使用多少个网格块来离散化储层。通常,这个数字很大,反问题是不恰当的。 TSVD方法对问题进行了正则化,并大大减少了解决该问题所需的计算量。为了计算TSVD,我们使用了Lanczos方法,并结合了问题的导数和伴随公式的数值实现。

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