Earth scientists will always be confronted with making decisions based on limited data sets. Therefore it is important to understand how to maximise geological interpretations from sparse data sets, while understanding the limitations of what can be inferred. This course explores how to combine various 3D spatial data sets to solve problems in 3D geological settings and examines the development of geological conceptual site models for quantification and communication. Topics covered include: basic statistics, introduction to scripting with python, gridding algorithms, 3D geological computer models of aquifers and reservoirs, gridding of faulted and folded geological data, geostatistical simulation, facies modelling, optimisation of data collection and the quantification of uncertainty between sampled locations. Case studies from regional hydrogeology, reservoir geology and contaminated sites will be presented.