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Optimally convergent mixed finite element methods for the time-dependent 2D/3D stochastic closed-loop geothermal system with multiplicative noise

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Abstract

In this paper, a new time-dependent 2D/3D stochastic closed-loop geothermal system with multiplicative noise is developed and studied. This model considers heat transfer between the free flow in the pipe region and the porous media flow in the porous media region. Darcy’s law and stochastic Navier-Stokes equations are used to control the flows in the pipe and porous media regions, respectively. The heat equation is coupled with the flow equation to describe the heat transfer in these both regions. In order to avoid sub-optimal convergence, a new mixed finite element method is proposed by using the Helmholtz decomposition that drives the multiplicative noise. Then, the stability of the proposed method is proved, and we obtain the optimal convergence order \(o(\Delta t^{\frac{1}{2}}+h)\) of global error estimation. Finally, numerical results indicate the efficiency of the proposed model and the accuracy of the numerical method.

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Data Availability

The datasets generated during and analysed during the current study are available from the corresponding author on reasonable request.

References

  1. Bundschuh, J., Arriaga, M.C.S.: Introduction to the Numerical Modeling of Groundwater and Geothermal Systems: Fundamentals of Mass, Energy and Solute Transport in Poroelastic Rocks, CRC Press, Boca Raton, FL, USA, (2010)

  2. Lund, J.W., Boyd, T.L.: Direct utilization of geothermal energy 2015 worldwide review. Geothermics. 60, 66–93 (2016)

    Article  Google Scholar 

  3. Bezyan, B., Porkhial, S., Mehrizi, A.A.: 3-D simulation of heat transfer rate in geothermal pile-foundation heat exchangers with spiral pipe configuration. Appl. Therm. Eng. 87, 655–668 (2015)

    Article  Google Scholar 

  4. Hecht-M’endez, J., Paly, M.D., Beck, M., et al.: Optimization of energy extraction for vertical closed-loop geothermal systems considering groundwater flow. Energy Convers. Manag. 66, 1–10 (2013)

    Article  Google Scholar 

  5. Oldenburg, C.M., Pan, L., Muir, M.P., et al.: Numerical Simulation of Critical Factors Controlling Heat Extraction from Geothermal Systems Using a Closed-Loop Heat Exchange Method, Proceedings, 41st Workshop on Geothermal Reservoir Engineering. Stanford University, Stanford, California (2016)

    Google Scholar 

  6. Wu, B.S., Ma, T.S., Feng, G.H., et al.: An approximate solution for predicting the heat extraction and preventing heat loss from a closed-loop geothermal reservoir. Geofluids. 2017, 1–17 (2017)

    Google Scholar 

  7. Cao, L.L., He, Y.N., Li, J.: A parallel Robin-Robin domain decomposition method based on modified characteristic FEMs for the time-dependent Dual-porosity-Navier-Stokes model with the Beavers-Joseph interface condition. J. Sci. Comput. 90, 1–34 (2022)

    Article  MathSciNet  Google Scholar 

  8. Li, J.: Numerical Method of Navier-Stokes Equations for Incompressible Flows. Science Press, Beijing (2019). ((in Chinese))

    Google Scholar 

  9. Li, J., Bai, Y., Zhao, X.: Modern Numerical Methods for Mathematical Physics Equations. Science Press, Beijing (2022). ((in Chinese))

    Google Scholar 

  10. Li, J., Lin, X., Chen, Z.X.: Finite Volume Methods for the Incompressible Navier-Stokes Equations, SpringerVerlag, Berlin, Heidelberg, (2023)

  11. Cao, L.L., He, Y.N., Li, J., et al.: Decoupled modified characteristic FEMs for fully evolutionary Navier-Stokes-Darcy model with the Beavers-Joseph interface condition. J. Comput. Appl. Math. 383, 113128 (2021)

    Article  MathSciNet  Google Scholar 

  12. Li, J., Lin, X.L., Zhao, X.: Optimal estimates on stabilized finite volume methods for the incompressible Navier-Stokes model in three dimensions. Numer. Method Partial Diff. Equat. 35(1), 128–154 (2019)

    Article  MathSciNet  Google Scholar 

  13. Li, R., Gao, Y., Li, J., Chen, Z.X.: Discontinuous finite volume element method for a coupled non-stationary Stokes-Darcy problem. J. Sci. Comput. 74, 693–727 (2018)

    Article  MathSciNet  Google Scholar 

  14. Mahbub, M.A.A., He, X.M., Nasu, N.J., et al.: A coupled multiphysics model and a decoupled stabilized finite element method for the closed-loop geothermal system. SIAM J. Sci. Comput. 42(4), 951–982 (2020)

    Article  MathSciNet  Google Scholar 

  15. Qin, Y., Wang, Y.S., Li, J.: A variable time step time filter algorithm for the geothermal system. SIAM J. Numer. Analy. 60, 2781–2806 (2022)

    Article  MathSciNet  Google Scholar 

  16. Zhang, W., Li, J.: PDNNs: the parallel deep neural networks for the Navier-Stokes equations coupled with heat equation. International Journal For Numerical Method in Fluids. 14, 1–15 (2022)

    Google Scholar 

  17. Bensoussan, A., Temam, R.: Equations stochastiques du type Navier-Stokes. J. Funct. Anal. 13(2), 195–222 (1973)

    Article  Google Scholar 

  18. Bessaih, H., Millet, A.: On strong \(L^{2}\) convergence of time numerical schemes for the stochastic 2D Navier-Stokes equations. IMA J. Numer. Anal. 39, 2135–2167 (2018)

    Article  Google Scholar 

  19. Brzézniak, Z., Carelli, E., Prohl, A.: Finite element based discretizations of the incompressible Navier-Stokes equations with multiplicative random forcing. IMA J. Numer. Anal. 33(3), 771–824 (2013)

    Article  MathSciNet  Google Scholar 

  20. Carelli, E., Hausenblas, E., Prohl, A.: Time-splitting methods to solve the stochastic incompressible Stokes equations. Siam J. Numer. Anal. 50(6), 2917–2939 (2012)

    Article  MathSciNet  Google Scholar 

  21. Bensoussan, A.: Stochastic Navier-Stokes equations. Acta Applicandae. Mathematica. 38(3), 267–304 (1995)

    Google Scholar 

  22. Yu, J.P., Mahbub, M.A.A., Feng, S., et al.: Stabilized finite element method for the stationary mixed Stokes-Darcy problem. Advances in Difference Equations. 2018(1), 1–19 (2018)

    Article  MathSciNet  Google Scholar 

  23. Flandoli, F., Gatarek, D.: Martingale and stationary solutions for stochastic Navier-Stokes equations. Probab. Theory Relat. Fields. 102(3), 367–391 (1995)

    Article  MathSciNet  Google Scholar 

  24. Si, Z.Y., Wang, Y.X., Li, S.S.: Decoupled modified characteristics finite element method for the time dependent Navier-Stokes/Darcy problem. Math. Methods Appl. Sci. 37(9), 1392–1404 (2014)

    Article  MathSciNet  Google Scholar 

  25. Tambue, A., Mukam, J.D.: Strong convergence and stability of the semi-tamed and tamed Euler schemes for stochastic differential equations with jumps under non-global Lipschitz condition. Int. J. Numer. Anal. Model. 16(6), 847–872 (2019)

    MathSciNet  Google Scholar 

  26. Li, J., Chen, Z.X., He, Y.N.: A stabilized multi-level method for non-singular finite volume solutions of the stationary 3D Navier-Stokes equations. Numer. Math. 122(2), 279–304 (2012)

    Article  MathSciNet  Google Scholar 

  27. Li, J., Lin, X.L., Zhao, X.: Optimal estimates on stabilized finite volume methods for the incompressible Navier-Stokes model in three dimensions. Numerical Methods for Partial Differential Equations. 35(1), 128–154 (2019)

    Article  MathSciNet  Google Scholar 

  28. Li, R., Li, J., He, X.M., et al.: A stabilized finite volume element method for a coupled Stokes-Darcy problem. Appl. Numer. Math. 133, 2–24 (2017)

    Article  MathSciNet  Google Scholar 

  29. Mikulevicius, R., Rozovskii, B.L.: Stochastic Navier-Stokes equations for turbulent flows. SIAM J. Math. Anal. 35(5), 1250–1310 (2004)

    Article  MathSciNet  Google Scholar 

  30. Prato, G.D., Debussche, A.: Ergodicity for the 3D stochastic Navier-Stokes equations. Journal de Mathematiques Pures et Appliquees. 82(8), 877–947 (2003)

    Article  MathSciNet  Google Scholar 

  31. Debussche, A., Odasso, C.: Markov solutions for the 3D stochastic Navier-Stokes equations with state dependent noise. J. Evol. Equ. 6(2), 305–324 (2006)

    Article  MathSciNet  Google Scholar 

  32. Hofmanová, M., Zhu, R., Zhu, X.: Global-in-time probabilistically strong and Markov solutions to stochastic 3D Navier-Stokes equations: Existence and non-uniqueness. arXiv:2104.09889 (2021)

  33. Hofmanová, M., Zhu, R., Zhu, X.: Non-unique ergodicity for deterministic and stochastic 3D Navier-Stokes and Euler equations. arXiv:2208.08290v1 (2022)

  34. Langa, J.A., Real, J., Simon, J.: Existence and Regularity of the Pressure for the Stochastic Navier-Stokes Equations. Appl. Math. Optim. 48(3), 195–210 (2003)

    Article  MathSciNet  Google Scholar 

  35. Feng, X.B., Qiu, H.L.: Analysis of fully discrete mixed finite element methods for time-dependent stochastic stokes equations with multiplicative noise. J. Sci. Comput. 88(2), (2021)

  36. Feng, X.B., Prohl, A., Vo, L.: Optimally convergent mixed finite element methods for the stochastic Stokes equations. IMA J. Numer. Anal. 41(3), 2280–2310 (2021)

    Article  MathSciNet  Google Scholar 

  37. Temam, R.: Navier-Stokes Equations. North-Holland, Amsterdam, New York (1984)

    Google Scholar 

  38. Li, S., Hou, Y.R.: A fully discrete stabilized finite element method for the time-dependent Navier-Stokes equations. Appl. Math. Comput. 215(1), 85–99 (2009)

    Article  MathSciNet  Google Scholar 

  39. Li, J., Liu, Q., Yue, J.: Numerical analysis of fully discrete finite element methods for the stochastic Navier-Stokes equations with multiplicative noise. Appl. Numer. Math. 170, 398–417 (2021)

    Article  MathSciNet  Google Scholar 

  40. Rybak, I., Magiera, J.: A multiple-time-step technique for coupled free flow and porous medium systems. J. Comput. Phys. 272(5), 327–342 (2014)

    Article  MathSciNet  Google Scholar 

  41. Wan, D.C., Patnaik, B.S.V., Wei, G.W.: A new benchmark quality solution for the buoyancy-driven cavity by discrete singular convolution. Numerical Heat Transfer Part B Fundamentals. 40(3), 199–228 (2001)

    Article  Google Scholar 

  42. Manzari, M.T.: An explicit finite element algorithm for convective heat transfer problems. International Journal of Numerical Methods for Heat and Fluid Flow. 9(8), 860–877 (1999)

    Article  MathSciNet  Google Scholar 

  43. Zhang, Y.Z., Hou, Y.R., Zheng, H.B.: A finite element variational multiscale method for steady-state natural convection problem based on two local gauss integrations. Numerical Methods for Partial Differential Equations. 30(2), 361–375 (2013)

    Article  MathSciNet  Google Scholar 

  44. Zhang, Y.Z., Hou, Y.R., Zhao, J.P.: Error analysis of a fully discrete finite element variational multiscale method for the natural convection problem. Computers and Mathematics with Applications. 68(4), 543–567 (2014)

    Article  MathSciNet  Google Scholar 

  45. Langa, J.A., Real, J., Simon, J.: Existence and Regularity of the Pressure for the Stochastic Navier-Stokes Equations. Appl. Math. Optim. 48, 195–210 (2003)

    Article  MathSciNet  Google Scholar 

  46. Temam, R.: Navier-Stokes Equations: Theory and Numerical Analysis. North-Holland, Amsterdam (1984)

    Google Scholar 

  47. Burns, J.A., He, X.M., Hu, W.: Feedback stabilization of a thermal fluid system with mixed boundary control, in honor of Max Gunzburger’s 70th birthday. Computers and Mathematics with Applications. 71, 2170–2191 (2016)

    Article  MathSciNet  Google Scholar 

  48. Hirata, S.C., Goyeau, B., Gobin, D., et al.: Linear stability of natural convection in superposed fluid and porous layers: Influence of the interfacial modeling. Int. J. Heat Mass Transfer. 50, 1356–1367 (2007)

    Article  Google Scholar 

  49. Layton, W.J., Yotov, S.I.: Coupling fluid flow with porous media flow. SIAM J. Numer. Anal. 40(6), 2195–2195 (2002)

    Article  MathSciNet  Google Scholar 

  50. Brezzi, F., Douglas, J., Marini, L.D.: Two families of mixed elements for second order elliptic problems. Numer. Math. 47, 217–235 (1985)

    Article  MathSciNet  Google Scholar 

  51. Mu, M., Zhu, X.H.: Decoupled schemes for a non-stationary mixed Stokes-Darcy model. Math. Comput. 79(270), 707–731 (2009)

    Article  MathSciNet  Google Scholar 

  52. Choi, W., Ooka, R.: Effect of natural convection on thermal response test conducted in saturated porous formation: Comparison of gravel-backfilled and cement-grouted borehole heat exchangers. Renew. Energy. 96, 891–903 (2016)

    Article  Google Scholar 

  53. Oldenburg, C.M., Pan, L., Muir, M.P., et al: Numerical simulation of critical factors controlling heat extraction from geothermal systems using a closed-loop heat exchange method, in Proceedings of the 41st Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, CA, 1-8 (2016)

  54. Girault, V., Raviart, P.A: Finite Element Methods for Navier-Stokes Equations, Springer, New York (1986)

  55. Qiu, C.X., He, X.M., Li, J., Lin, Y.P.: A domain decomposition method for the time-dependent Navier-Stokes-Darcy model with Beavers-Joseph interface condition and defective boundary condition. J. Comput. Phys. 411(15), 109400 (2020)

    Article  MathSciNet  Google Scholar 

  56. Li, J., Yue, J., Zhang, W., Duan, W.S.: The deep learning Galerkin method for the general Stokes equations. J. Sci. Comput. 93, 1–20 (2022)

    Article  MathSciNet  Google Scholar 

  57. He, X.M., Li, J., Lin, Y.P., Ming, J.: A domain decomposition method for the steady-state Navier-Stokes-Darcy model with Beavers-Joseph interface condition. SIAM J. Sci. Comput. 37(5), 264–290 (2015)

    Article  MathSciNet  Google Scholar 

  58. Li, J., Zeng, J.Y., Li, R.: An adaptive discontinuous finite volume element method for the Allen-Cahn equation. Advanced in Computational Mathematics. 49(4), 55 (2023)

    Article  MathSciNet  Google Scholar 

  59. Li, J., Chen, Z.X.: On the semi-discrete stabilized finite volume method for the transient Navier?Stokes equations. Adv. Comput. Math. 38(2), 281–320 (2013)

    Article  MathSciNet  Google Scholar 

  60. Li, J., Chen, Z.X.: Optimal \(L^2\), \(H^1\) and \(L^\infty \) analysis of finite volume methods for the stationary Navier-Stokes equations with large data. Numer. Math. 126(1), 75–101 (2014)

    Article  MathSciNet  Google Scholar 

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Correspondence to Jian Li.

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Communicated by: Silas Alben

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Supported in part by NSF of China (No. 11771259 and No. 12001347), Shaanxi Provincial Joint Laboratory of Artificial Intelligence (No. 2022JC-SYS-05), Innovative team project of Shaanxi Provincial Department of Education (No. 21JP013 and No. 21JP019), Shaanxi Province Natural Science basic research program key project (No. 2023-JC-ZD-02), National High-end Foreign Experts Recruitment Plan (No. G2023041032L), Energy Mathematics and Data Fusion Key Laboratory of Higher Education in Shaanxi Province, Shaanxi Provincial Demonstration Base for the Introduction of Foreign Intelligence: Mathematics and data science cross-integration innovation and intelligence introduction base.

A Appendix

A Appendix

Proof of Theorem 3.2. In (2.32) - (2.35), let \(t=t_{n+1}\) and \(t=t_{n}\), and then make the difference. Subtract (3.1) - (3.6) from the resulting formula and define \(a_{f}^{n+1}\!=\!\textbf{u}_{f}(t_{n+1})\!-\textbf{u}_{f}^{n+1},b_{f}^{n+1}\!=\!R(t_{n+1})\!-r_{f}^{n+1}, c_{f}^{n+1}\!=\!\theta _{f}(t_{n+1})\!-\theta _{f}^{n+1}; a_{p}^{n+1}\!=\textbf{u}_{p}(t_{n+1})-\textbf{u}_{p}^{n+1},b_{p}^{n}\!=\phi _{p}(t_{n+1})\!-\phi _{p}^{n+1}, c_{p}^{n}\!=\!\theta _{p}(t_{n+1})-\theta _{p}^{n+1}\), we get

$$\begin{aligned}{} & {} (a_{f}^{n+1}-a_{f}^{n},\textbf{v}_{f})_{\Omega _{f}} +Pr\int _{t_{n}}^{t_{n+1}}\big (\nabla (\textbf{u}_{f}(s)-\textbf{u}_{f}^{n+1}),\nabla \textbf{v}_{f}\big )_{\Omega _{f}}ds\nonumber \\{} & {} +(c_{f}^{n+1}-c_{f}^{n},\varphi )_{\Omega _{f}}+k_{f}\int _{t_{n}}^{t_{n+1}}\big (\nabla (\theta _{f}(s)-\theta _{f}^{n+1}),\nabla \varphi \big )_{\Omega _{f}}ds\nonumber \\{} & {} +\int _{t_{n}}^{t_{n+1}}\big (c(\textbf{u}_{f}(s),\textbf{u}_{f}(s),\textbf{v}_{f})_{\Omega _{f}}-c(\textbf{u}_{f}^{n},\textbf{u}_{f}^{n+1},\textbf{v}_{f})_{\Omega _{f}}\big ]ds\nonumber \\{} & {} +\int _{t_{n}}^{t_{n+1}}\big (t_{f}(\textbf{u}_{f}(s),\theta _{f}(s),\varphi )_{\Omega _{f}}-t_{f}(\textbf{u}_{f}^{n},\theta _{f}^{n+1},\varphi )_{\Omega _{f}}\big ]ds\nonumber \\{} & {} -k_{f}\int _{t_{n}}^{t_{n+1}}\bigg [\int _{\uppercase {i}}\hat{n}_{f}\cdot \nabla (\theta _{f}(s)-\theta _{f}^{n})\varphi dl\bigg ]ds\nonumber \\{} & {} +\frac{k_{f}\gamma }{h}\int _{t_{n}}^{t_{n+1}}\bigg [\int _{\uppercase {i}}(\theta _{f}(s)\!-\!\theta _{p}(s)\!-\!\theta _{f}^{n+1}\!+\!\theta _{p}^{n})\varphi dl\bigg ]ds \!+\!C_{a}Da(a_{p}^{n+1}\!-\!a_{p}^{n},\textbf{v}_{p})_{\Omega _{p}}\nonumber \\{} & {} +Pr\int _{t_{n}}^{t_{n+1}}\big (\textbf{u}_{p}(s)-\textbf{u}_{p}^{n+1},\textbf{v}_{p}\big )_{\Omega _{p}}ds +(c_{p}^{n+1}-c_{p}^{n},\omega )_{\Omega _{p}}\nonumber \\{} & {} +k_{p}\int _{t_{n}}^{t_{n+1}}\big (\nabla (\theta _{p}(s)-\theta _{p}^{n+1}),\nabla \omega \big )_{\Omega _{p}}ds +\int _{t_{n}}^{t_{n+1}}\big (t_{p}(\textbf{u}_{p}(s),\theta _{p}(s),\omega )_{\Omega _{p}}\nonumber \\{} & {} -t_{p}(\textbf{u}_{p}^{n},\theta _{p}^{n+1},\omega )_{\Omega _{p}}\big ]ds +k_{f}\int _{t_{n}}^{t_{n+1}}\bigg [\int _{\uppercase {i}}\hat{n}_{f}\cdot \nabla (\theta _{f}(s)-\theta _{f}^{n})\omega dl\bigg ]ds\nonumber \\{} & {} -\frac{k_{f}\gamma }{h}\int _{t_{n}}^{t_{n+1}}\bigg [\int _{\uppercase {i}}(\theta _{f}(s)-\theta _{p}(s)-\theta _{f}^{n+1}+\theta _{p}^{n+1})\omega dl\bigg ]ds\nonumber \\= & {} PrRa\mathbf {\xi }\int _{t_{n}}^{t_{n+1}}(\theta _{f}(s)-\theta _{f}^{n},\textbf{v}_{f})_{\Omega _{f}}ds +PrDaRa\mathbf {\xi }\int _{t_{n}}^{t_{n+1}}(\theta _{p}(s)-\theta _{p}^{n},\textbf{v}_{p})_{\Omega _{p}}ds\nonumber \\{} & {} +\bigg (\int _{t_{n}}^{t_{n+1}}\big (\mathbf {\varepsilon }(s)-\mathbf {\varepsilon }^{n},\textbf{u}_{f}^{n})\big )dW(s),\textbf{v}_{f}\bigg )_{\Omega _{f}} +\int _{t_{n}}^{t_{n+1}}(\textbf{f}_{f}(s)-\textbf{f}_{f}(t_{n+1}),a_{f}^{n+1})ds.\nonumber \\ \end{aligned}$$
(A.1)

Taking \(\textbf{v}_{f}=2a_{f}^{n+1},\varphi =2c_{f}^{n+1};\textbf{v}_{p}=2a_{p}^{n+1},\omega =2c_{p}^{n+1}\), and using the identity \(2(a-b,a)=a^{2}-b^{2}+(a-b)^{2}\), we find that

$$\begin{aligned}{} & {} \parallel a_{f}^{n+1}\parallel _{L^{2}(\Omega _{f})}^{2}-\parallel a_{f}^{n}\parallel _{L^{2}(\Omega _{f})}^{2} +\parallel a_{f}^{n+1}-a_{f}^{n}\parallel _{L^{2}(\Omega _{f})}^{2}+2\Delta tPr\parallel \nabla a_{f}^{n+1}\parallel _{L^{2}(\Omega _{f})}^{2}\nonumber \\{} & {} +\parallel c_{f}^{n+1}\parallel _{L^{2}(\Omega _{f})}^{2}-\parallel c_{f}^{n}\parallel _{L^{2}(\Omega _{f})}^{2} +\parallel c_{f}^{n+1}-c_{f}^{n}\parallel _{L^{2}(\Omega _{f})}^{2}+2\Delta tk_{f}\parallel \nabla c_{f}^{n+1}\parallel _{L^{2}(\Omega _{f})}^{2}\nonumber \\{} & {} +C_{a}Da\parallel a_{p}^{n+1}\parallel _{L^{2}(\Omega _{p})}^{2}-C_{a}Da\parallel a_{p}^{n}\parallel _{L^{2}(\Omega _{p})}^{2} +C_{a}Da\parallel a_{p}^{n+1}-a_{p}^{n}\parallel _{L^{2}(\Omega _{p})}^{2}\nonumber \\{} & {} +2\Delta tPr\parallel a_{p}^{n+1}\parallel _{L^{2}(\Omega _{p})}^{2} +\parallel c_{p}^{n+1}\parallel _{L^{2}(\Omega _{p})}^{2}-\parallel c_{p}^{n}\parallel _{L^{2}(\Omega _{p})}^{2} +\parallel c_{p}^{n+1}-c_{p}^{n}\parallel _{L^{2}(\Omega _{p})}^{2}\nonumber \\{} & {} +2\Delta tk_{p}\parallel \nabla c_{p}^{n+1}\parallel _{L^{2}(\Omega _{p})}^{2}\nonumber \\\le & {} \!-2Pr\int _{t_{n}}^{t_{n+1}}\!\!\big (\nabla (\textbf{u}_{f}(s)\!-\!\textbf{u}_{f}(t_{n+1})),\nabla a_{f}^{n+1}\big )_{\Omega _{f}}ds\!-\!2k_{f}\int _{t_{n}}^{t_{n+1}}\!\big (\nabla (\theta _{f}(s)\!-\!\theta _{f}(t_{n+1})),\nabla c_{f}^{n+1}\big )_{\Omega _{f}}ds\nonumber \\{} & {} -2Pr\int _{t_{n}}^{t_{n+1}}\big (\textbf{u}_{p}(s)-\textbf{u}_{p}(t_{n+1}),a_{p}^{n+1}\big )_{\Omega _{p}}ds -2k_{p}\int _{t_{n}}^{t_{n+1}}\big (\nabla (\theta _{p}(s)-\theta _{p}(t_{n+1})),\nabla c_{p}^{n+1}\big )_{\Omega _{p}}ds\nonumber \\{} & {} +2k_{f}\int _{t_{n}}^{t_{n+1}}\bigg [\int _{\uppercase {i}}\hat{n}_{f} \cdot \nabla (\theta _{f}(s)-\theta _{f}^{n})(c_{f}^{n+1}-c_{p}^{n+1})dl\bigg ]ds-\frac{2k_{f}\gamma }{h}\int _{t_{n}}^{t_{n+1}}\bigg [\int _{\uppercase {i}} (\theta _{f}(s)-\theta _{p}(s)\nonumber \\{} & {} -\theta _{f}^{n+1}+\theta _{p}^{n})c_{f}^{n+1}dl\bigg ]ds +\frac{2k_{f}\gamma }{h}\int _{t_{n}}^{t_{n+1}}\bigg [\int _{\uppercase {i}} (\theta _{f}(s)-\theta _{p}(s)-\theta _{f}^{n+1}+\theta _{p}^{n+1})c_{p}^{n+1}dl\bigg ]ds\nonumber \\{} & {} +2PrRa\mathbf {\xi }\int _{t_{n}}^{t_{n+1}}\big (\theta _{f}(s)-\theta _{f}^{n},a_{f}^{n+1}\big )_{\Omega _{f}}ds+2PrDaRa\mathbf {\xi }\int _{t_{n}}^{t_{n+1}}\big (\theta _{p}(s)-\theta _{p}^{n},a_{p}^{n+1}\big )_{\Omega _{p}}ds\nonumber \\{} & {} +2\bigg (\int _{t_{n}}^{t_{n+1}}\big (\mathbf {\varepsilon }(s)-\mathbf {\varepsilon }^{n}\big )dW(s),a_{f}^{n+1}\bigg )_{\Omega _{p}}+\int _{t_{n}}^{t_{n+1}}(\textbf{f}_{f}(s)-\textbf{f}_{f}(t_{n+1}),a_{f}^{n+1})ds\nonumber \\{} & {} \!+2\int _{t_{n}}^{t_{n+1}}\!\big [c(\textbf{u}_{f}(s),\textbf{u}_{f}(s),a_{f}^{n+1})_{\Omega _{f}} \!-\!c(\textbf{u}_{f}^{n},\textbf{u}_{f}^{n+1},a_{f}^{n+1})_{\Omega _{f}}\!\big ]ds \!+\!2\int _{t_{n}}^{t_{n+1}}\!\big [t_{f}(\textbf{u}_{f}(s),\!\theta _{f}(s),\!c_{f}^{n+1})_{\Omega _{f}}\nonumber \\{} & {} -t_{f}(\textbf{u}_{f}^{n},\theta _{f}^{n+1},c_{f}^{n+1})_{\Omega _{f}}\big ]ds+2\int _{t_{n}}^{t_{n+1}}\big [t_{p}(\textbf{u}_{p}(s),\theta _{p}(s),c_{p}^{n+1})_{\Omega _{p}} -t_{p}(\textbf{u}_{p}^{n},\theta _{p}^{n+1},c_{p}^{n+1})_{\Omega _{p}}\big ]ds.\nonumber \\ \end{aligned}$$
(A.2)

Using the Cauchy-Schwarz inequality, the Young inequality and (2.36), yields

$$\begin{aligned}{} & {} \!-2Pr\int _{t_{n}}^{t_{n+1}}\!\big (\nabla (\textbf{u}_{f}(s)\!-\!\textbf{u}_{f}(t_{n+1})),\nabla a_{f}^{n+1}\big )_{\Omega _{f}}ds \!\le \!\frac{\Delta tPr}{4}\!\parallel \nabla a_{f}^{n+1}\!\parallel _{L^{2}(\Omega _{f})}^{2}+C\Delta t,\nonumber \\ \end{aligned}$$
(A.3)
$$\begin{aligned}{} & {} \!-2k_{f}\int _{t_{n}}^{t_{n+1}}\!\big (\nabla (\theta _{f}(s)\!-\!\theta _{f}(t_{n+1})),\nabla c_{f}^{n+1}\big )_{\Omega _{f}}ds\! \le \!\frac{\Delta tk_{f}}{2}\!\parallel \nabla c_{f}^{n+1}\!\parallel _{L^{2}(\Omega _{f})}^{2}+C\Delta t,\nonumber \\\end{aligned}$$
(A.4)
$$\begin{aligned}{} & {} \!-2Pr\int _{t_{n}}^{t_{n+1}}\!\big (\textbf{u}_{p}(s)\!-\!\textbf{u}_{p}(t_{n+1}),a_{p}^{n+1}\big )_{\Omega _{p}}ds\! \le \!\frac{\Delta tPr}{2}\!\parallel a_{p}^{n+1}\!\parallel _{L^{2}(\Omega _{p})}^{2}+C\Delta t, \end{aligned}$$
(A.5)
$$\begin{aligned}{} & {} \!-2k_{p}\int _{t_{n}}^{t_{n+1}}\!\big (\nabla (\theta _{p}(s)\!-\theta _{p}(t_{n+1})),\nabla c_{p}^{n+1}\big )_{\Omega _{p}}ds \!\le \!\frac{\Delta tk_{p}}{2}\!\parallel \nabla c_{p}^{n+1}\!\parallel _{L^{2}(\Omega _{p})}^{2}+C\Delta t.\nonumber \\\end{aligned}$$
(A.6)
$$\begin{aligned}{} & {} \!\int _{t_{n}}^{t_{n+1}}(\textbf{f}_{f}(s)\!-\textbf{f}_{f}(t_{n+1}),a_{f}^{n+1})_{\Omega _{f}}ds \le \parallel a_{f}^{n+1}\parallel _{L^{2}(\Omega _{f})}^{2}+C\Delta t. \end{aligned}$$
(A.7)

As for the trilinear term, we can bound

$$\begin{aligned}{} & {} 2\int _{t_{n}}^{t_{n+1}}\big [c(\textbf{u}_{f}(s),\textbf{u}_{f}(s),a_{f}^{n+1})_{\Omega _{f}} -c(\textbf{u}_{f}^{n},\textbf{u}_{f}^{n+1},a_{f}^{n+1})_{\Omega _{f}}\big ]ds\\= & {} 2\int _{t_{n}}^{t_{n+1}}\big [c(\textbf{u}_{f}(s),\textbf{u}_{f}(s),a_{f}^{n+1})_{\Omega _{f}} -c(\textbf{u}_{f}(t_{n}),\textbf{u}_{f}(t_{n+1)},a_{f}^{n+1})_{\Omega _{f}}\big ]ds\\{} & {} +2\int _{t_{n}}^{t_{n+1}}\big [c(\textbf{u}_{f}(t_{n}),\textbf{u}_{f}(t_{n+1)},a_{f}^{n+1})_{\Omega _{f}} -c(\textbf{u}_{f}^{n},\textbf{u}_{f}^{n+1},a_{f}^{n+1})_{\Omega _{f}}\big ]ds\\ \end{aligned}$$
$$\begin{aligned}= & {} 2\int _{t_{n}}^{t_{n+1}}\!\big [c(\textbf{u}_{f}(s)\!-\textbf{u}_{f}(t_{n}),\textbf{u}_{f}(s),a_{f}^{n+1})_{\Omega _{f}} \!+c(\textbf{u}_{f}(t_{n}),\textbf{u}_{f}(s)\!-\textbf{u}_{f}(t_{n+1)},a_{f}^{n+1})_{\Omega _{f}}\big ]ds\nonumber \\{} & {} +2\int _{t_{n}}^{t_{n+1}}c(a_{f}^{n},\textbf{u}_{f}(t_{n+1)},a_{f}^{n+1})_{\Omega _{f}}ds\nonumber \\\le & {} Pr\Delta t\parallel \nabla a_{f}^{n+1}\parallel _{L^{2}(\Omega _{f})}^{2}+C\Delta t, \end{aligned}$$
(A.8)

Similarly, we can get

$$\begin{aligned}{} & {} 2\int _{t_{n}}^{t_{n+1}}\big [t_{f}(\textbf{u}_{f}(s),\theta _{f}(s),c_{f}^{n+1})_{\Omega _{f}} -t_{f}(\textbf{u}_{f}^{n},\theta _{f}^{n+1},c_{f}^{n+1})_{\Omega _{f}}\big ]ds \nonumber \\\le & {} \frac{k_{f}\Delta t}{2}\parallel \nabla c_{f}^{n+1}\parallel _{L^{2}(\Omega _{f})}^{2} +C\Delta t\Vert a_{f}^{n}\Vert _{L^{2}(\Omega _{f})}^{2} +C\Delta t,\end{aligned}$$
(A.9)
$$\begin{aligned}{} & {} 2\int _{t_{n}}^{t_{n+1}}\big [t_{p}(\textbf{u}_{p}(s),\theta _{p}(s),c_{p}^{n+1})_{\Omega _{p}} -t_{p}(\textbf{u}_{p}^{n},\theta _{p}^{n+1},c_{p}^{n+1})_{\Omega _{p}}\big ]ds\nonumber \\\le & {} \frac{k_{p}\Delta t}{2}\parallel \nabla c_{p}^{n+1}\parallel _{L^{2}(\Omega _{p})}^{2} +C\Delta t\Vert a_{p}^{n}\Vert _{L^{2}(\Omega _{p})}^{2} +C\Delta t. \end{aligned}$$
(A.10)

Applying the trace inequality, the inverse inequality and (2.36), we obtain

$$\begin{aligned}{} & {} 2k_{f}\int _{t_{n}}^{t_{n+1}}\bigg [\int _{\uppercase {i}}\hat{n}_{f} \cdot \nabla (\theta _{f}(s)-\theta _{f}^{n})(c_{f}^{n+1}-c_{p}^{n+1})dl\bigg ]ds\nonumber \\= & {} 2k_{f}\int _{t_{n}}^{t_{n+1}}\!\bigg [\int _{\uppercase {i}}\hat{n}_{f} \cdot \nabla (\theta _{f}(s)\!-\!\theta _{f}(t_{n}))(c_{f}^{n+1}\!-\!c_{p}^{n+1})dl\bigg ]ds \!+\!2k_{f}\int _{t_{n}}^{t_{n+1}}\!\bigg [\!\int _{\uppercase {i}}\hat{n}_{f} \cdot \nabla c_{f}^{n}(c_{f}^{n+1}-c_{p}^{n+1})dl\bigg ]ds\nonumber \\\le & {} \frac{4k_{f}C_{inv}\Delta t}{\gamma }\parallel \nabla c_{f}^{n}\parallel _{L^{2}(\Omega _{f})}^{2} +\frac{k_{f}\gamma \Delta t}{2h}\parallel c_{f}^{n+1}-c_{p}^{n+1}\parallel _{L^{2}(\uppercase {i})}^{2} +C\Delta t, \end{aligned}$$
(A.11)
$$\begin{aligned}{} & {} -\frac{2k_{f}\gamma }{h}\int _{t_{n}}^{t_{n+1}}\bigg [\int _{\uppercase {i}} (\theta _{f}(s)-\theta _{p}(s)-\theta _{f}^{n+1}+\theta _{p}^{n})c_{f}^{n+1}dl\bigg ]ds\nonumber \\{} & {} +\frac{2k_{f}\gamma }{h}\int _{t_{n}}^{t_{n+1}}\bigg [\int _{\uppercase {i}} (\theta _{f}(s)-\theta _{p}(s)-\theta _{f}^{n+1}+\theta _{p}^{n+1})c_{p}^{n+1}dl\bigg ]ds\nonumber \\= & {} -\frac{2k_{f}\gamma \Delta t}{h}\int _{\uppercase {i}}(c_{f}^{n+1}-c_{p}^{n})c_{f}^{n+1}dl +\frac{2k_{f}\gamma \Delta t}{h}\int _{\uppercase {i}}(c_{f}^{n+1}-c_{p}^{n+1})c_{p}^{n+1}dl -\frac{2k_{f}\gamma \Delta t}{h}\int _{\uppercase {i}}(\theta _{p}(t_{n+1})\nonumber \\{} & {} -\theta _{p}(t_{n}))c_{f}^{n+1}dl\nonumber \\\le & {} -\frac{2k_{f}\gamma \Delta t}{h}\parallel c_{f}^{n+1}-c_{p}^{n+1}\parallel _{L^{2}(\uppercase {i})}^{2} -\frac{k_{f}\gamma \Delta t}{h}\big [\parallel c_{p}^{n+1}\parallel _{L^{2}(\uppercase {i})}^{2}-\parallel c_{p}^{n}\parallel _{L^{2}(\uppercase {i})}^{2} -\parallel c_{f}^{n+1}\nonumber \\{} & {} -c_{p}^{n+1}\parallel _{L^{2}(\uppercase {i})}^{2}\big ]+\frac{4k_{f}C_{inv}\Delta t}{\gamma }\Vert \nabla c_{f}^{n+1}\Vert _{L^{2}(\Omega _{f})}^{2}+C\Delta t. \end{aligned}$$
(A.12)

Thanks to the Cauchy-Schwarz inequality, the Young’s inequality and (2.36), yield the following inequalities

$$\begin{aligned}{} & {} 2PrRa\mathbf {\xi }\int _{t_{n}}^{t_{n+1}}\big (\theta _{f}(s)-\theta _{f}^{n},a_{f}^{n+1}\big )_{\Omega _{f}}ds\nonumber \\= & {} 2PrRa\mathbf {\xi }\int _{t_{n}}^{t_{n+1}}\big (\theta _{f}(s)-\theta _{f}(t_{n}),a_{f}^{n+1}\big )_{\Omega _{f}}ds +2PrRa\mathbf {\xi }\int _{t_{n}}^{t_{n+1}}\big (\theta _{f}(t_{n})-\theta _{f}^{n},a_{f}^{n+1}\big )_{\Omega _{f}}ds\nonumber \\\le & {} 4PrRa^{2}\Delta t\parallel c_{f}^{n+1}\parallel _{L^{2}(\Omega _{f})}^{2} +\frac{1}{4}Pr\Delta t\parallel \nabla a_{f}^{n+1}\parallel _{L^{2}(\Omega _{f})}^{2} +2PrRa\Delta t\parallel a_{f}^{n+1}\parallel _{L^{2}(\Omega _{f})}^{2}+C\Delta t,\nonumber \\ \end{aligned}$$
(A.13)
$$\begin{aligned}{} & {} 2PrDaRa\mathbf {\xi }\int _{t_{n}}^{t_{n+1}}\big (\theta _{p}(s)-\theta _{p}^{n},a_{p}^{n+1}\big )_{\Omega _{p}}ds\\\le & {} 2PrRa^{2}Da^{2}\Delta t\parallel c_{p}^{n+1}\parallel _{L^{2}(\Omega _{p})}^{2} \!+\frac{1}{2}Pr\Delta t\parallel a_{p}^{n+1}\parallel _{L^{2}(\Omega _{p})}^{2} \!+2PrDaRa\Delta t\parallel a_{p}^{n+1}\parallel _{L^{2}(\Omega _{p})}^{2}+C\Delta t.\nonumber \end{aligned}$$
(A.14)

By the definition of the martingale, (2.27), (2.20) and (2.36), we can get

$$\begin{aligned}{} & {} 2\bigg (\int _{t_{n}}^{t_{n+1}}\big (\mathbf {\varepsilon }(s)-\mathbf {\varepsilon }^{n}\big )dW(s),a_{f}^{n+1}\bigg )_{\Omega _{p}}\nonumber \\= & {} 2\bigg (\!\int _{t_{n}}^{t_{n+1}}\big (B(s,\textbf{u}_{f}(s))\!-\!B(t_{n},\textbf{u}_{f}^{n})\big )dW(s),a_{f}^{n+1}\!-\!a_{f}^{n}\bigg )_{\Omega _{p}} \!+\!2\bigg (\!\int _{t_{n}}^{t_{n+1}}\big (b(s)\!-\!b^{n}\big )dW(s),a_{f}^{n+1}\!-\!a_{f}^{n}\!\bigg )_{\Omega _{p}}\nonumber \\\le & {} \frac{1}{2}\Vert a_{f}^{n+1}-a_{f}^{n}\Vert _{L^{2}(\Omega _{f})}^{2} +C\Delta t\Vert a_{f}^{n}\Vert _{L^{2}(\Omega _{f})}^{2} +C\Delta t^{2}\parallel a_{f}^{n}\parallel _{L^{2}(\Omega _{f})}^{2}+C\Delta t^{3}. \end{aligned}$$
(A.15)

Substitute (A.3) - (A.15) into (A.2), taking the sum from \(n=0\) to \(l-1\), using Gronwall’s lemma, and taking the expectation, we obtain

$$\begin{aligned}{} & {} E\big [\parallel a_{f}^{l}\parallel _{L^{2}(\Omega _{f})}^{2}\big ] +\frac{1}{2}E\bigg [\sum _{n=0}^{l-1}\parallel a_{f}^{n+1}-a_{f}^{n}\parallel _{L^{2}(\Omega _{f})}^{2}\bigg ] +\frac{\Delta tPr}{2}E\bigg [\sum _{n=0}^{l-1}\parallel \nabla a_{f}^{n+1}\parallel _{L^{2}(\Omega _{f})}^{2}\bigg ]\nonumber \\{} & {} +E\big [\!\parallel c_{f}^{l}\!\parallel _{L^{2}(\Omega _{f})}^{2}\!\big ] \!+E\bigg [\!\sum _{n=0}^{l-1}\!\parallel c_{f}^{n+1}\!-c_{f}^{n}\parallel _{L^{2}(\Omega _{f})}^{2}\!\bigg ] \!+\Delta tk_{f}\Big (1\!-\frac{8C_{inv}}{\gamma }\Big )E\bigg [\sum _{n=0}^{l-1}\!\parallel \nabla c_{f}^{n+1}\!\parallel _{L^{2}(\Omega _{f})}^{2}\!\bigg ]\nonumber \\{} & {} +C_{a}DaE\big [\!\parallel a_{p}^{l}\!\parallel _{L^{2}(\Omega _{p})}^{2}\big ] \!+C_{a}DaE\bigg [\!\sum _{n=0}^{l-1}\parallel a_{p}^{n+1}\!-\!a_{p}^{n}\parallel _{L^{2}(\Omega _{p})}^{2}\!\bigg ] \!+\Delta tPrE\bigg [\!\sum _{n=0}^{l-1}\!\parallel a_{p}^{n+1}\!\parallel _{L^{2}(\Omega _{p})}^{2}\!\bigg ]\nonumber \\{} & {} +E\big [\parallel c_{p}^{l}\parallel _{L^{2}(\Omega _{p})}^{2}\big ] +E\bigg [\sum _{n=0}^{l-1}\parallel c_{p}^{n+1}-c_{p}^{n}\parallel _{L^{2}(\Omega _{p})}^{2}\bigg ] +\Delta tk_{p}E\bigg [\sum _{n=0}^{l-1}\parallel \nabla c_{p}^{n+1}\parallel _{L^{2}(\Omega _{p})}^{2}\bigg ]\nonumber \\{} & {} +\frac{k_{f}\gamma \Delta t}{h}E\big [\parallel c_{p}^{l}\parallel _{L^{2}(\Omega _{p})}^{2}\big ] +\frac{k_{f}\gamma \Delta t}{4h}E\bigg [\sum _{n=0}^{l-1}\parallel c_{f}^{n+1}-c_{p}^{n+1}\parallel _{L^{2}(\uppercase {i})}^{2}\bigg ]\nonumber \\\le & {} C\Delta t, \end{aligned}$$
(A.16)

where \(\gamma >8C_{inv}\). Thus we prove that (3.11).

Decoupling (2.32), let \(t=t_{n+1}\) and \(t=t_{n}\), and then make the difference. Subtract (3.1) from the resulting formula to get

$$\begin{aligned}{} & {} \int _{t_{n}}^{t^{n+1}}(R(s)-r_{f}^{n+1},\nabla \cdot \textbf{v}_{f})_{\Omega _{f}}ds\nonumber \\= & {} (a_{f}^{n+1}\!-\!a_{f}^{n},\textbf{v}_{f})_{\Omega _{f}} \!+\!Pr\!\int _{t_{n}}^{t^{n+1}}\!\!\big (\nabla (\textbf{u}_{f}(s)\!-\textbf{u}_{f}^{n+1}),\nabla \textbf{v}_{f}\big )_{\Omega _{f}}ds \!+\!\int _{t_{n}}^{t^{n+1}}\!\!\big [c(\textbf{u}_{f}(s),\textbf{u}_{f}(s),a_{f}^{n+1})_{\Omega _{f}}\nonumber \\{} & {} \!-c(\textbf{u}_{f}^{n},\textbf{u}_{f}^{n+1},a_{f}^{n+1})_{\Omega _{f}}\big ]ds \!-PrRa\int _{t_{n}}^{t^{n+1}}\!\!(\theta _{f}(s)\!-\theta _{f}^{n},\textbf{v}_{f})_{\Omega _{f}}ds\nonumber \\{} & {} \!+\bigg (\!\int _{t_{n}}^{t^{n+1}}\!\!(\textbf{f}_{f}(s)\!-\textbf{f}_{f}(t_{n+1}))ds,\textbf{v}_{f}\bigg )_{\Omega _{f}}-\bigg (\int _{t_{n}}^{t^{n+1}}\big (\mathbf {\varepsilon }(s)-\mathbf {\varepsilon }^{n}\big )dW(s),\textbf{v}_{f}\!\bigg )_{\Omega _{f}}. \end{aligned}$$
(A.17)

Thus, sum from n=0 to \(l-1\) of the above equations, using the Cauchy-Schwarz inequality, (A.3), (A.8) and (A.15), we gain

$$\begin{aligned}{} & {} \bigg (\sum _{n=0}^{l-1}\int _{t_{n}}^{t^{n+1}}(R(s)-r_{f}^{n+1})ds,\nabla \cdot \textbf{v}_{f}\bigg )_{\Omega _{f}}\nonumber \\= & {} \sum _{n=0}^{l-1}(a_{f}^{n+1}-a_{f}^{n},\textbf{v}_{f})_{\Omega _{f}} +Pr\sum _{n=0}^{l-1}\int _{t_{n}}^{t^{n+1}}\big (\nabla (\textbf{u}_{f}(s)-\textbf{u}_{f}^{n+1}),\nabla \textbf{v}_{f}\big )_{\Omega _{f}}ds\nonumber \\{} & {} +\sum _{n=0}^{l-1}\int _{t_{n}}^{t^{n+1}}\big [c(\textbf{u}_{f}(s),\textbf{u}_{f}(s),a_{f}^{n+1})_{\Omega _{f}} -c(\textbf{u}_{f}^{n},\textbf{u}_{f}^{n+1},a_{f}^{n+1})_{\Omega _{f}}\big ]ds\nonumber \\{} & {} -PrRa\mathbf {\xi }\sum _{n=0}^{l-1}\int _{t_{n}}^{t^{n+1}}(\theta _{f}(s)-\theta _{f}^{n},\textbf{v}_{f})_{\Omega _{f}}ds -\sum _{n=0}^{l-1}\bigg (\int _{t_{n}}^{t^{n+1}}(\textbf{f}_{f}(s)-\textbf{f}_{f}(t_{n+1}))ds,\textbf{v}_{f}\bigg )_{\Omega _{f}}\nonumber \\{} & {} -\sum _{n=0}^{l-1}\bigg (\int _{t_{n}}^{t^{n+1}}\big (\mathbf {\varepsilon }(s)-\mathbf {\varepsilon }^{n})\big )dW(s),\textbf{v}_{f}\bigg )_{\Omega _{f}}\nonumber \\\le & {} \bigg [\Big (\sum _{n=0}^{l-1}\parallel a_{f}^{n+1}-a_{f}^{n}\parallel _{L^{2}(\Omega _{f})}^{2}\Big )^{\frac{1}{2}} +Pr\Big (\sum _{n=0}^{l-1}\Delta t\parallel \nabla (\textbf{u}_{f}(s)-\textbf{u}_{f}(t_{n+1}))\parallel _{L^{2}(\Omega _{f})}^{2}\Big )^{\frac{1}{2}}\nonumber \\{} & {} +Pr\Big (\sum _{n=0}^{l-1}\Delta t\parallel \nabla a_{f}^{n+1}\parallel _{L^{2}(\Omega _{f})}^{2}\Big )^{\frac{1}{2}}+C\bigg (\Delta t\sum _{n=0}^{l-1}\Vert \nabla \textbf{u}_{f}(t_{n+1})\Vert _{L^{2}(\Omega _{f})}^{2}\Vert \nabla a_{f}^{n+1}\Vert _{L^{2}(\Omega _{f})}^{2}\bigg )^{\frac{1}{2}}\nonumber \\{} & {} +PrRa\Big (\sum _{n=0}^{l-1}\Delta t\parallel \theta _{f}(s)-\theta _{f}(t_{n})\parallel _{L^{2}(\Omega _{f})}^{2}\Big )^{\frac{1}{2}}+PrRa\Big (\sum _{n=0}^{l-1}\Delta t\parallel c_{f}^{n+1}\parallel _{L^{2}(\Omega _{f})}^{2}\Big )^{\frac{1}{2}}\nonumber \\{} & {} +\Big (\sum _{n=0}^{l-1}\Delta t\parallel \textbf{f}_{f}(s)-\textbf{f}_{f}(t_{n+1})\parallel _{L^{2}(\Omega _{f})}^{2}\Big )^{\frac{1}{2}}\bigg ] \bigg (\sum _{n=0}^{l-1}\parallel \nabla \textbf{v}_{f}^{n+1}\parallel _{L^{2}(\Omega _{f})}^{2}\bigg )^{\frac{1}{2}}. \end{aligned}$$
(A.18)

Taking the expectation of the above inequality and using the inf-sup condition, we can obtain

$$\begin{aligned} E\bigg [\int _{0}^{T}R(s)ds-\Delta t\sum _{n=0}^{l-1}r_{f}^{n+1}\bigg ]\le C\Delta t^{\frac{1}{2}}. \end{aligned}$$
(A.19)

which implies (3.11).

Decoupling (2.32), let \(t=t_{n+1}\) and \(t=t_{n}\), and then make the difference. Subtract (3.4) from the resulting formula to get

$$\begin{aligned}{} & {} C_{a}Da(a_{p}^{n+1}\!-a_{p}^{n},\textbf{v}_{p})_{\Omega _{p}}\!+Pr\int _{t_{n}}^{t^{n+1}}(\textbf{u}_{p}(s)\!-\textbf{u}_{p}^{n+1},\textbf{v}_{p})_{\Omega _{p}} \!-\!Da\int _{t_{n}}^{t^{n+1}}(\phi _{p}(s)-\phi _{p}^{n+1},\nabla \cdot \textbf{v}_{p})_{\Omega _{p}}\nonumber \\= & {} PrDaRa\mathbf {\xi }\int _{t_{n}}^{t^{n+1}}(\theta _{p}(s)-\theta _{p}^{n},\textbf{v}_{p})_{\Omega _{p}}. \end{aligned}$$
(A.20)

Thus, sum from \(n=0\) to \(l-1\) of the above equations, using the Cauchy-Schwarz inequality and (A.5), we gain

$$\begin{aligned}{} & {} Da\bigg (\sum _{n=0}^{l-1}\int _{t_{n}}^{t^{n+1}}(\phi _{p}(s)-\phi _{p}^{n+1})ds,\nabla \cdot \textbf{v}_{p}\bigg )_{\Omega _{p}}\nonumber \\= & {} C_{a}Da\sum _{n=0}^{l-1}(a_{p}^{n+1}-a_{p}^{n},\textbf{v}_{p})_{\Omega _{p}} +Pr\sum _{n=0}^{l-1}\int _{t_{n}}^{t^{n+1}}(\textbf{u}_{p}(s)-\textbf{u}_{p}^{n+1},\textbf{v}_{p})_{\Omega _{p}}ds\nonumber \\{} & {} +PrDaRa\mathbf {\xi }\sum _{n=0}^{l-1}\int _{t_{n}}^{t^{n+1}}(\theta _{p}^{n}-\theta _{p}(s),\textbf{v}_{p})_{\Omega _{p}}ds\nonumber \\\le & {} \bigg [\!C_{a}Da\Big (\sum _{n=0}^{l-1}\parallel a_{p}^{n+1}\!-\!a_{p}^{n}\parallel _{L^{2}(\Omega _{p})}^{2}\Big )^{\frac{1}{2}} \!+\!Pr\Big (\sum _{n=0}^{l-1}\Delta t\parallel \textbf{u}_{p}(s)\!-\!\textbf{u}_{p}(t_{n+1})\parallel _{L^{2}(\Omega _{p})}^{2}\!\Big )^{\frac{1}{2}}\nonumber \\{} & {} +Pr\Big (\sum _{n=0}^{l-1}\Delta t\parallel a_{p}^{n+1}\parallel _{L^{2}(\Omega _{p})}^{2}\Big )^{\frac{1}{2}} \!+\!PrDaRa\Big (\sum _{n=0}^{l-1}\Delta t\!\parallel \theta _{p}(s)\!-\!\theta _{p}(t_{n})\parallel _{L^{2}(\Omega _{p})}^{2}\Big )^{\frac{1}{2}}\nonumber \\{} & {} +PrDaRa\Big (\sum _{n=0}^{l-1}\Delta t\parallel c_{p}^{n}\parallel _{L^{2}(\Omega _{p})}^{2}\!\Big )^{\frac{1}{2}}\bigg ] \Big (\sum _{n=0}^{l-1}\Delta t\parallel \textbf{v}_{p}\parallel _{L^{2}(\Omega _{p})}^{2}\Big )^{\frac{1}{2}}. \end{aligned}$$
(A.21)

Taking the expectation of the above inequality and using the inf-sup condition, we can obtain

$$\begin{aligned} E\bigg [\int _{0}^{T}\phi _{p}(s)ds-\Delta t\sum _{n=0}^{l-1}\phi _{p}^{n+1}\bigg ]\le C\Delta t^{\frac{1}{2}}. \end{aligned}$$
(A.22)

At this point, the proof of 3.12 is complete.

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Gao, X., Qin, Y. & Li, J. Optimally convergent mixed finite element methods for the time-dependent 2D/3D stochastic closed-loop geothermal system with multiplicative noise. Adv Comput Math 50, 46 (2024). https://doi.org/10.1007/s10444-024-10122-x

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