Advanced inverse modelling and stochastic representations of heterogeneous porous and fractured media
Objective: provide advanced knowledge and practice in hydrogeophysical inverse modelling and modern geostatistical representations and modelling of subsurface heterogeneity. Data acquired in the two field based workshops (1 and 2) will be used as a case study.
- Formulating and solving the inverse problem: deterministic and probabilistic perspectives on inverse modelling,
- Incorporation of prior knowledge and error sources, petrophysical and structural approaches to joint inversion
- Basic concepts in geostatistics: fundamentals, spatial correlation and variogram analysis, interpolation and kriging
- Simulation versus estimation: why geostatistical simulation?, the Monte Carlo framework, kriging to condition a simulation
- Multivariate problems: continuous versus categorical data, cross-variograms, co-kriging and co-simulations
- When multigaussian models are insufficient: sequential Indicator Simulations (SIS), transition probabilities (TProgs), multiple-point statistics (MPS), which geostatistical model for which purpose?
- Industrial case studies in petroleum reservoir (Jef Caers, STAN), in water resources and geothermal systems (AQUA , SHS)