Research

Our research has a broad spectrum, but key ingredients are the applied nature, aiming for practical impact, at the same time relying on foundational development in data scientific methods. Our publication list provides an overview of the various academic contributions. In addition, we work closely with Earth Resources companies and government entities to define specific collaborative sponsored projects. Some recent company projects are listed below as well as our current student research topics.

Groundwater management in Denmark (Danish Government)
Production planning for a structurally complex reservoir in Libya (Wintershall)
Reservoir appraisal for a deep-water turbidite reservoir from seismic data in West Africa (Hess)
Designing uranium contaminant remediation in the USA (SE3)
Big data predictive analytics for optimizing shale reservoirs (Anadarko, Repsol, NGI)
Assessment of low-enthalpy geothermal systems for heating buildings (Belgian government)
A strategy for rapid & realistic forecasting of reservoir performance using process-based models (ENI)
Direct forecasting and uncertainty updating at the appraisal stage without building new models (Chevron)
Implicit dynamic uncertainty for automation of data fusion & prediction in mineral resources evaluation and planning (BHP)
Multiple-point geostatistics and bayesian evidential learning for gas reservoir management (Edison)

Featured Research

David Zhen Yin

Automated uncertainty quantification of geological model using Bayesian Evidential Learning

Examples of student research topics

Assessing oil migration pathways in petroleum systems

Marcelo Silka
Automated uncertainty quantification of geological model using Bayesian Evidential Learning

David Zhen Yin
Bayesian evidential learning

Jef Caers
Building informative priors and fast simulation methods for subsurface flow applications

Erik Nesvold
Combining data science methods with flow simulation in shale resources development

Alexander Bakay
Conditioning categorical models to hard data using a Gibbs sampling of a truncated multi-variate Gaussian model

Francky Fouedijo
Groundwater management in Denmark

Jef Caers, Celine Scheidt, Troels Vilhelmsen
Learning from big data for rapid uncertainty quantification of exploratory ore deposits

Liang Yang
Mapping incised-valley-fill deposits in the Central Valley

Alex Miltenberger
Monitoring low-enthalpy heating systems using time-lapse ERT

Jef Caers, Thomas Hermans
Optimization of decision-making in the context of CO2 sequestration monitoring

Clothilde Venereau
Optimization under uncertainty for enhanced geothermal systems

Ahinoam (Noe) Pollack
Predicting favorable locations for geothermal development

Noah Athens
Quantifying uncertainty in geological boundary modeling for mineral resource estimation: application to a porphyry copper deposit

Francky Fouedijo
Quantifying uncertainty on flow and transport of nitrate using geophysical data in the Danish aquifer system

Lijing Wang
Quantifying uncertainty using level sets with stochastic motion

Jef Caers, Liang Yang
Recognition of sub-resolution stacking patterns from seismic data

Riyad Muradov
Seismic reservoir property estimation and uncertainty quantification with statistical learning techniques

Anshuman Pradhan
Uncertainty quantification and global sensitivity analysis for reactive transport models, application to uranium remediation

Jef Caers, Kate Maher