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Geophysics-Based Fluid-Facies Predictions Using Ensemble Updating of Binary State Vectors
Mathematical Geosciences ( IF 2.8 ) Pub Date : 2021-02-08 , DOI: 10.1007/s11004-021-09922-4
Margrethe Kvale Loe , Dario Grana , Håkon Tjelmeland

Fluid flow simulations are commonly used to predict the fluid displacement in subsurface reservoirs; however, model validation is challenging due to the lack of direct measurements. Geophysical data can be used to monitor the displacement of the fluid front. The updating of the fluid front location in two-phase flow problems based on time-lapse geophysical data can be formulated as an inverse problem, specifically a data assimilation problem, where the state is a vector of binary variables representing the fluid-facies and the observations are measurements of continuous geophysical properties, such as electrical or elastic properties. In geosciences, many data assimilation problems are solved using ensemble-based methods relying on the Kalman filter approach. However, for discrete variables, such approaches cannot be applied due to the Gaussian-linear assumption. An innovative approach for mixed discrete-continuous problems based on ensemble updating of binary state vectors is presented for fluid-facies prediction problems with time-lapse geophysical properties. The proposed inversion method is demonstrated in a synthetic two-dimensional simulation example where water is injected into a reservoir and hydrocarbon is produced. Resistivity values obtained from controlled-source electromagnetic data are assumed to be available at different times. According to the results, the proposed inversion method is to a large extent able to reproduce the true underlying binary field of fluid-facies.



中文翻译:

基于二元状态向量集合更新的基于地球物理学的流相预测

流体模拟通常用于预测地下储层中的流体驱替。然而,由于缺乏直接测量,模型验证具有挑战性。地球物理数据可用于监测流体锋面的位移。可以将基于时移地球物理数据的两相流问题中流体前沿位置的更新公式化为反问题,特别是数据同化问题,其中状态是代表流体相和流体的二元变量的矢量观测是对连续地球物理性质(例如电性质或弹性性质)的测量。在地球科学中,许多数据同化问题都是使用基于卡尔曼滤波方法的基于集成的方法来解决的。但是,对于离散变量,由于高斯线性假设,这种方法无法应用。针对具有时移地球物理特征的流体相预测问题,提出了一种基于二进制状态向量的整体更新的混合离散连续问题的创新方法。在合成的二维模拟示例中演示了所提出的反演方法,在该示例中,将水注入了储层并产生了碳氢化合物。从受控源电磁数据获得的电阻率值假定在不同时间可用。根据结果​​,所提出的反演方法在很大程度上能够再现流体相的真实底层二进制场。针对具有时移地球物理特征的流体相预测问题,提出了一种基于二进制状态向量的整体更新的混合离散连续问题的创新方法。在合成的二维模拟示例中演示了所提出的反演方法,在该示例中,将水注入了储层并产生了碳氢化合物。从受控源电磁数据获得的电阻率值假定在不同时间可用。根据结果​​,所提出的反演方法在很大程度上能够再现流体相的真实底层二进制场。针对具有时移地球物理特征的流体相预测问题,提出了一种基于二进制状态向量的整体更新的混合离散连续问题的创新方法。在合成的二维模拟示例中演示了所提出的反演方法,在该示例中,将水注入了储层并产生了碳氢化合物。从受控源电磁数据获得的电阻率值假定在不同时间可用。根据结果​​,所提出的反演方法在很大程度上能够再现流体相的真实底层二进制场。在合成的二维模拟示例中演示了所提出的反演方法,在该示例中,将水注入了储层并产生了碳氢化合物。从受控源电磁数据获得的电阻率值假定在不同时间可用。根据结果​​,所提出的反演方法在很大程度上能够再现流体相的真实底层二进制场。在合成的二维模拟示例中演示了所提出的反演方法,在该示例中,将水注入了储层并产生了碳氢化合物。从受控源电磁数据获得的电阻率值假定在不同时间可用。根据结果​​,所提出的反演方法在很大程度上能够再现流体相的真实底层二进制场。

更新日期:2021-02-08
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