Joint geostatistical simulation techniques are used to quantify uncertainty for spatially
correlated attributes, including mineral deposits, petroleum reservoirs, hydrogeological …

This work develops a new approach for delineating sites that are contaminated by multiple
soil heavy metals and applies it to a case study. First a number of contaminant sample data …

To speed up multivariate geostatistical simulation it is common to transform the set of
attributes into spatially uncorrelated factors that can be simulated independently. Spatial …

Multiple variables that are correlated should be jointly simulated and the resulting
realizations should reproduce the experimental data statistics (ie histogram, variogram …

Uncertainty quantification is an important topic for many environmental studies, such as
identifying zones where potentially toxic materials exist in the soil. In this work, the …

Remediation prioritization frequently falls short of systematically evaluating the underlying
ecological value of different sites. This study presents a novel approach to delineating sites …

In the geostatistical treatment of multivariate data sets the joint modelling of their spatial
continuity is usually required. While it is possible to automate the inference of a suitable …

Variability of the rock properties and the uncertainty associated with their estimation in the
blocks mined and processed becloud the decision making in the mining value chain. In …

This thesis developed a novel adaptive methodology for the optimal design of additional
sampling based on a geostatistical model that can preserve both multivariate non-linearity …