Bayesian Poroelastic Aquifer Characterization From InSAR Surface Deformation Data. Part I: Maximum A Posteriori Estimate-Reference-Cited by-同舟云学术

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Bayesian Poroelastic Aquifer Characterization From InSAR Surface Deformation Data. Part I: Maximum A Posteriori Estimate

Published:2020-10 Issue:10 Volume:56 Page:
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resour. Res.

Author:

Alghamdi Amal¹^ORCID,Hesse Marc A.¹²^ORCID,Chen Jingyi²³^ORCID,Ghattas Omar¹²⁴

Affiliation:

1. Oden Institute for Computational Engineering and Sciences University of Texas at Austin Austin TX USA

2. Geological Sciences University of Texas at Austin Austin TX USA

3. Aerospace Engineering & Engineering Mechanics University of Texas at Austin Austin TX USA

4. Mechanical Engineering University of Texas at Austin Austin TX USA

Funder

U.S. Department of Energy

National Science Foundation

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2020WR027391

Reference81 articles.

1. A-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems with Regularized $\ell_0$-Sparsification

2. A Fast and Scalable Method for A-Optimal Design of Experiments for Infinite-dimensional Bayesian Nonlinear Inverse Problems

3. Mean-Variance Risk-Averse Optimal Control of Systems Governed by PDEs with Random Parameter Fields Using Quadratic Approximations

4. Sensing the ups and downs of Las Vegas: InSAR reveals structural control of land subsidence and aquifer-system deformation

5. Hessian-based model reduction for large-scale systems with initial-condition inputs

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4. InSAR-observed surface deformation in New Mexico’s Permian Basin shows threats and opportunities presented by leaky injection wells;Scientific Reports;2023-10-12

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