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High-Dimensional Groundwater Flow Inverse Modeling by Upscaled Effective Model on Principal Components
Water Resources Research ( IF 5.4 ) Pub Date : 2022-07-11 , DOI: 10.1029/2022wr032610
Yue Zhao 1 , Quan Guo 1 , Chunhui Lu 2 , Jian Luo 1
Affiliation  

The main computational costs of gradient-based inverse methods for high-resolution groundwater flow inverse problems include costly forward model simulations and the large number of such simulations required to determine the Jacobian matrix. We develop an upscaling-based inverse approach, named upscaled principal component inverse approach (UPCIA), which achieves dimensionality reduction and reduces computational cost of forward model simulations by evaluating the Jacobian through upscaled effective models on a coarse-resolution grid constructed from upscaled principal components. UPCIA integrates downscaling into the inverse problem by estimating principal component coefficients based on the coarse-resolution forward model, which are then used to generate high-resolution parameter fields. Various numerical experiments demonstrate the effectiveness and efficiency of UPCIA, including 2-D/3-D high-dimensional steady-state and transient hydraulic tomography with known storativity to estimate multi-Gaussian transmissivity or hydraulic conductivity fields. Results show that the hydraulic head is insensitive to small-scale variability of conductivity, and UPCIA provides high-quality inversion results similar to inverse methods with high-resolution forward model simulations and significantly reduces computation time by orders of magnitude. In addition to supporting the characterization of heterogeneity in sufficient detail, UPCIA can also be used to examine whether finer resolution is necessary and possibly to determine an optimal inverse resolution.

中文翻译:

主成分放大有效模型的高维地下水流反演

用于高分辨率地下水流反演问题的基于梯度的反演方法的主要计算成本包括昂贵的正向模型模拟以及确定雅可比矩阵所需的大量此类模拟。我们开发了一种基于放大的逆方法,称为放大的主成分逆方法(UPCIA),它通过在由放大的主成分构成的粗分辨率网格上通过放大的有效模型评估雅可比来实现降维并降低正向模型模拟的计算成本. UPCIA 通过基于粗分辨率前向模型估计主成分系数,将降尺度集成到逆问题中,然后将其用于生成高分辨率参数字段。各种数值实验证明了 UPCIA 的有效性和效率,包括 2-D/3-D 高维稳态和瞬态水力层析成像,具有已知的储存能力,以估计多高斯透射率或水力传导率场。结果表明,水头对电导率的小尺度变化不敏感,而 UPCIA 提供了类似于具有高分辨率正向模型模拟的反演方法的高质量反演结果,并显着减少了计算时间几个数量级。除了足够详细地支持异质性的表征外,UPCIA 还可用于检查是否需要更精细的分辨率,并可能确定最佳的逆分辨率。包括 2-D/3-D 高维稳态和瞬态水力层析成像,具有已知的储水性,以估计多高斯透射率或水力传导率场。结果表明,水头对电导率的小尺度变化不敏感,而 UPCIA 提供了类似于具有高分辨率正向模型模拟的反演方法的高质量反演结果,并显着减少了计算时间几个数量级。除了足够详细地支持异质性的表征外,UPCIA 还可用于检查是否需要更精细的分辨率,并可能确定最佳的逆分辨率。包括 2-D/3-D 高维稳态和瞬态水力层析成像,具有已知的储水性,以估计多高斯透射率或水力传导率场。结果表明,水头对电导率的小尺度变化不敏感,而 UPCIA 提供了类似于具有高分辨率正向模型模拟的反演方法的高质量反演结果,并显着减少了计算时间几个数量级。除了足够详细地支持异质性的表征外,UPCIA 还可用于检查是否需要更精细的分辨率,并可能确定最佳的逆分辨率。结果表明,水头对电导率的小尺度变化不敏感,而 UPCIA 提供了类似于具有高分辨率正向模型模拟的反演方法的高质量反演结果,并显着减少了计算时间几个数量级。除了足够详细地支持异质性的表征外,UPCIA 还可用于检查是否需要更精细的分辨率,并可能确定最佳的逆分辨率。结果表明,水头对电导率的小尺度变化不敏感,而 UPCIA 提供了类似于具有高分辨率正向模型模拟的反演方法的高质量反演结果,并显着减少了计算时间几个数量级。除了足够详细地支持异质性的表征外,UPCIA 还可用于检查是否需要更精细的分辨率,并可能确定最佳的逆分辨率。
更新日期:2022-07-11
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