气候变化领域集成服务门户(CCPortal): Fast Stokes Flow Simulations for Geophysical-Geodynamic Inverse Problems and Sensitivity Analyses Based On Reduced Order Modeling

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DOI	10.1029/2019JB018314
	Fast Stokes Flow Simulations for Geophysical-Geodynamic Inverse Problems and Sensitivity Analyses Based On Reduced Order Modeling
	Ortega-Gelabert O.; Zlotnik S.; Afonso J.C.; Díez P.
发表日期	2020
ISSN	21699313
卷号	125 期号:3
英文摘要	Markov chain Monte Carlo (MCMC) methods have become standard in Bayesian inference and multi-observable inversions in almost every discipline of the Earth sciences. In the case of geodynamic and/or coupled geophysical-geodynamic inverse problems, however, the computational cost associated with the solution of large-scale 3-D Stokes forward problems has rendered probabilistic formulations impractical. Here we present a novel and extremely efficient method to produce ultrafast solutions of the 3-D Stokes problem for MCMC simulations. Our approach combines the individual benefits of Reduced Basis techniques, goal-oriented error formulations, and MCMC algorithms to produce an accurate and computationally efficient surrogate for the forward problem. Importantly, the surrogate adapts itself during the MCMC simulation according to the history of the chain and the goals of the inversion. This maximizes the efficiency of the forward problem and removes the need for preinversion off-line computations to build a surrogate. We demonstrate the benefits and limitations of the method with several numerical examples and show that in all cases the computational cost is of the order of <1% compared to a traditional MCMC approach. The method is general enough to be applied to a range of problems, including uncertainty quantification/propagation, adjoint-based geodynamic inversions, sensitivity analyses in mantle convection problems, and in the creating surrogate models for complex forward problems (e.g., heat transfer, seismic tomography, and magnetotellurics). ©2020. American Geophysical Union. All Rights Reserved.
英文关键词	mantle convection; probabilistic inversion; reduced order model
语种	英语
来源期刊	Journal of Geophysical Research: Solid Earth
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/187906
作者单位	Laboratori de Càlcul Numèric (LaCàN), Departament d'Enginyeria Civil i Ambiental, Universitat Politècnica de Catalunya, Barcelona, Spain; Department of Earth and Planetary Sciences, Macquarie University, Sydney, Australia; Centre for Earth Evolution and Dynamics, Department of Geosciences, University of Oslo, Oslo, Norway
推荐引用方式 GB/T 7714	Ortega-Gelabert O.,Zlotnik S.,Afonso J.C.,et al. Fast Stokes Flow Simulations for Geophysical-Geodynamic Inverse Problems and Sensitivity Analyses Based On Reduced Order Modeling[J],2020,125(3).
APA	Ortega-Gelabert O.,Zlotnik S.,Afonso J.C.,&Díez P..(2020).Fast Stokes Flow Simulations for Geophysical-Geodynamic Inverse Problems and Sensitivity Analyses Based On Reduced Order Modeling.Journal of Geophysical Research: Solid Earth,125(3).
MLA	Ortega-Gelabert O.,et al."Fast Stokes Flow Simulations for Geophysical-Geodynamic Inverse Problems and Sensitivity Analyses Based On Reduced Order Modeling".Journal of Geophysical Research: Solid Earth 125.3(2020).