3D Multi-Physics Uncertainty Quantification using Physics-Based Machine Learning

3D multi-physics uncertainty quantification using physics-based machine learning

Benefits of Global Sensitivity Analysis and Reduced Order Modeling for Basin-Scale Process Simulations

Certified Reduced Basis Method in Geosciences Addressing the challenge of high dimensional problems

preprint

Certified reduced basis method in geosciences

scholarly article

Crustal-Scale Thermal Models: Revisiting the Influence of Deep Boundary Conditions

preprint

Crustal-Scale Thermal Models: Revisiting the Influence of Deep Boundary Conditions

Crustal-scale thermal models: revisiting the influence of deep boundary conditions

scholarly article

Deep geothermal: The ‘Moon Landing’ mission in the unconventional energy and minerals space

article published in 2015

GemPy 1.0: open-source stochastic geological modeling and inversion

scientific article published in 2019

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

preprint

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

How well do we know our models?

Making sense of Isogeometric Analysis for geothermal applications: Parametric geomodelling (NURBS) for fast model construction, simulation and adaptation

Pattern Extraction of Topsoil and Subsoil Heterogeneity and Soil‐Crop Interaction Using Unsupervised Bayesian Machine Learning: An Application to Satellite‐Derived NDVI Time Series and Electromagnetic Induction Measurements

scientific article published in 2019

Perspectives of Physics-Based Machine Learning for Geoscientific Applications Governed by Partial Differential Equations

Physics-based machine learning for modeling thermo-hydraulic processes in a coaxial deep borehole heat exchanger, considering an explicit reservoir-wellbore representation: A case study of Cornwall, UK  

Productivity enhancement of geothermal wells through fault zones: Efficient numerical evaluation of a parameter space for the Upper Jurassic aquifer of the North Alpine Foreland Basin

Quantifying Geodynamical Influences through Physics-Based Machine Learning: A Case Study from the Alpine Region 

The Application of Neural Operator in subsurface process simulation 

The Surface Velocity Response of a Tropical Glacier to Intra and Inter Annual Forcing, Cordillera Blanca, Peru

scientific article published in 2021

The Value of Scientific Machine Learning for Geothermal Applications

Uncertainty Quantification for Basin-Scale Conductive Models

Uncertainty Quantification for Basin-Scale Geothermal Conduction Models

Uncertainty quantification for basin-scale geothermal conduction models

scientific article published on 10 March 2022

Uncertainty quantification with a physics-based machine learning method for geothermal-well targeting: A case study of The Hague, Netherlands

Water Table Uncertainties due to Uncertainties in Structure and Properties of an Unconfined Aquifer

scientific article published on 29 August 2017