Global sensitivity analysis to optimize basin-scale conductive model calibration: A case study from the Upper Rhine Graben

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

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Calibrating geothermal simulations is a critical step, both in scientific and industrial contexts, with suitable model parameterizations being optimized to reduce discrepancies between simulated and measured temperatures. Here we present a methodology to identify model errors in the calibration and compensate for 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 (reduced basis method), reducing computation time by several orders of magnitude.
Original languageEnglish
Article number102143
JournalGeothermics
Volume95
DOIs
Publication statusPublished - Sep 2021

Keywords

  • Global sensitivity analysis
  • Sensitivity-driven model calibration
  • Upper Rhine Graben
  • Reduced basis method

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