Global Sensitivity Analysis to Optimize Basin-Scale Conductive Model Calibration - Insights on the Upper Rhine Graben

This is a Preprint and has not been peer reviewed.

Downloads

Download Preprint

Authors

Denise Degen , Karen Veroy, Jessica Freymark, Magdalena Scheck-Wenderoth, Florian Wellmann 

Abstract

Geothermal simulations are widely used in both scientific and applied industrial contexts. Typically, the temperature state is evaluated on the basis of the heat equation, with suitable parameterizations of the model domain and defined boundary conditions, which are calibrated to obtain a minimal misfit between measured and simulated temperature values. We demonstrate the essential need for global sensitivity studies for robust geothermal model calibrations since local studies overestimate the influence of the parameters. We ensure the feasibility of the study by using a physics-based machine learning approach, that reduces the computation time by several orders of magnitude.

DOI

https://doi.org/10.31223/osf.io/b7pgs

Subjects

Applied Mathematics, Earth Sciences, Physical Sciences and Mathematics

Keywords

global sensitivity analysis, reduced basis method, sensitivity-driven model calibration, Upper Rhine Graben

Dates

Published: 2020-04-01 16:04

Older Versions
License

CC BY Attribution 4.0 International

Add a Comment

You must log in to post a comment.


Comments

There are no comments or no comments have been made public for this article.