Global Sensitivity Analysis to Optimize Basin-Scale Conductive Model Calibration – A Case Study From the Upper Rhine Graben

This is a Preprint and has not been peer reviewed. This is version 2 of this Preprint.

Downloads

Download Preprint

Authors

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

Abstract

Calibrating geothermal simulations is a critical step, both in scientific and industrial contexts, with suitable model parameterizations being optimised to reduce discrepancies between simulated and measured temperatures. Here we present a methodology to identify unaccounted physical processes in the process and overcome the problem of measurement sparsity. With an application to the Upper Rhine Graben, we demonstrate the essential need for global sensitivity studies to robustly calibrate geothermal models, showing that local studies overestimate the influence of some parameters. We ensure the feasibility of the study through a physics-based machine learning approach, reducing 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: 2020-04-02 02:34

Last Updated: 2021-03-16 06:44

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.