Uncertainty Quantification for Basin-Scale Conductive Models

Abstract

Geophysical simulations are commonly used in many scientific studies. Especially in complex simulations, it is still common practice to provide a single deterministic outcome. Often, a probabilistic approach would be preferable, as a way to quantify and communicate uncertainties, but is infeasible due to long simulation times. We present here a method to generate full state predictions based on a reduced basis method that significantly reduces simulation time, thus enabling studies which require a large number of simulations, such as probabilistic simulations and inverse approaches. We implemented this approach in an existing simulation framework and showcase the application in a geothermal study, where we generate 2D and 3D predictive uncertainty maps. These maps allow a detailed model insight, identifying regions with both high temperatures and low uncertainties. Due to the flexible implementation, the methods are transferable to other geophysical simulations, where both the state and the uncertainty are important.

Authors 3

1. Denise Degen corresponding Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University

2. Karen Veroy

   Eindhoven University of Technology

   Affiliation as printed

   Eindhoven University of Technology

3. Florian Wellmann Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University