3D Ensemble Space Inversion and Nonstationary Geostats
This comprehensive tutorial demonstrates fast, efficient calibration of a complex 3D model. It complements a previous tutorial on a similar subject. However it shows how
This comprehensive tutorial demonstrates fast, efficient calibration of a complex 3D model. It complements a previous tutorial on a similar subject. However it shows how
Optimization under uncertainty is notoriously numerically intensive. However its numerical burden can be reduced if data space inversion (DSI) is used to construct a surrogate
Ensemble space inversion (ENSI) enables efficient, regularisation-constrained calibration of complex, highly-parameterised models. This tutorial demonstrates how linear analysis can be undertaken in partnership with the
Ensemble space inversion (ENSI) is implemented through the PEST_HP suite (version 18). Using ENSI you can calibrate a complex model quickly. The calibration subspace is comprised
Building and history-matching a three-dimensional model is a difficult procedure. The third dimension increases parameter requirements, model run times, and model output uncertainty. Ideally, predictive
This tutorial explores the use of “conceptual points” as a precursor to model parameterisation. Expected hydraulic properties are provided at these conceptual points. Just as
This tutorial explores construction of the interface between PEST/PEST++and a simple MODFLOW/MODPATH model, and how to then subject that model to history-matching and uncertainty analysis–including
View the webinar recording introducing the course here. This free guided self-study course and weekly Q & A sessions with the GMDSI team provided guidance and
Using the PLPROC parameter preprocessor supplied with the PEST suite, moveable polylinear and polygonal structural features such as faults and aquitard windows can be inserted
This tutorial introduces data space inversion (DSI). DSI can be used to explore the uncertainties of predictions made by complex models with complicated hydraulic property
GMDSI is managed by the National Centre for Groundwater Research and Training (NCGRT) and administered by Flinders University.