SAV Decoupled Ensemble Algorithm for the Dual‐Porosity‐Stokes Model With Uncertainty Quantification

ABSTRACT We present an ensemble algorithm for the dual‐porosity‐Stokes model with random intrinsic permeabilities in the matrix and microfracture. This model arises in various applications such as hydrology, industrial filtration, and petroleum extraction. Our algorithm combines a scalar auxiliary variable (SAV) approach, an ensemble idea, and a decoupled strategy to achieve high accuracy and efficiency. The SAV approach removes the stability restriction on the time‐step size. The ensemble idea reduces the storage and time cost of constructing coefficient matrices for different samples with random parameters. The decoupled strategy splits the dual‐porosity‐Stokes model into three simple systems (five sub‐problems) that can be solved independently by using the IMEX method. We prove that our algorithm is unconditionally long‐time stable and optimally convergent. We also demonstrate its performance and applications through three numerical experiments, especially a 3D model problem for the horizontal open‐hole completion wellbore.

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Publication Details

Journal
Numerical Methods for Partial Differential Equations
Published
2025-09-01
DOI
https://doi.org/10.1002/num.70037
Primary Topic
Advanced Numerical Methods in Computational Mathematics
Type
article
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article

SAV Decoupled Ensemble Algorithm for the Dual‐Porosity‐Stokes Model With Uncertainty Quantification

Shan Li, Haibiao Zheng, Yizhong Sun, Ziwei Liu
Numerical Methods for Partial Differential Equations
Advanced Numerical Methods in Computational Mathematics
article

SAV Decoupled Ensemble Algorithm for the Dual‐Porosity‐Stokes Model With Uncertainty Quantification

Shan Li, Haibiao Zheng, Yizhong Sun, Ziwei Liu
article en

Abstract

ABSTRACT We present an ensemble algorithm for the dual‐porosity‐Stokes model with random intrinsic permeabilities in the matrix and microfracture. This model arises in various applications such as hydrology, industrial filtration, and petroleum extraction. Our algorithm combines a scalar auxiliary variable (SAV) approach, an ensemble idea, and a decoupled strategy to achieve high accuracy and efficiency. The SAV approach removes the stability restriction on the time‐step size. The ensemble idea reduces the storage and time cost of constructing coefficient matrices for different samples with random parameters. The decoupled strategy splits the dual‐porosity‐Stokes model into three simple systems (five sub‐problems) that can be solved independently by using the IMEX method. We prove that our algorithm is unconditionally long‐time stable and optimally convergent. We also demonstrate its performance and applications through three numerical experiments, especially a 3D model problem for the horizontal open‐hole completion wellbore.

Numerical Methods for Partial Differential EquationsVol. 41(5)
Hong Kong Baptist University (HK), Shantou University (CN), East China Normal University (CN)
Openalex Percentile: Top 74%
Advanced Numerical Methods in Computational Mathematics
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SAV Decoupled Ensemble Algorithm for the Dual‐Porosity‐Stokes Model With Uncertainty Quantification — Shan Li, Haibiao Zheng, et al. · Numerical Methods for Partial Differential Equations (2025) | TGRS Research Map | TGRS