来年度よりポスドクとしてくるのを希望しているElvar(現the University of Auckland の博士課程)にセミナーを行ってもらいました。彼は、地熱貯留層モデリングのパラメータの最適化を専門としています。
Randomized Matrix Approximation Methods for Faster Inversion and Uncertainty Quantification of Geothermal Reservoir Models Elvar Karl Bjarkason (Engineering Science, The University of Auckland) Geothermal reservoir simulations are typically time-consuming, and models made up of a few tens of thousands of model blocks can easily take hours to run. This is a considerable hindrance to model development since current industry standard methods require running numerous simulations to invert or history-match a highly-parameterized geothermal model. Accurate uncertainty quantification is hindered to an even greater degree since it requires significantly more simulations. During the talk, we will discuss how randomized low-rank matrix approximation methods can be useful for speeding up inversion of highly-parameterized models. Finally, we will briefly demonstrate how the presented methods can be used to estimate parameter and predictive uncertainty of a geothermal model.