GEOSCIENCE DATA VISUALISATION IN 3D – AN APPLICATION AT A CONTAMINATED LAND SITE

Forecasting the spatial characteristics of contaminants in the sub-surface is an essential prerequisite in planning and designing a method for remediation. The distribution of these contaminants in the sub-surface is often largely controlled by the type and architecture of the geology. Understanding the relationships between the geology and contaminants can be used to optimise further site investigation and plan remediation strategies. Here we present a method to visualise geology and contaminant distribution in 3D.

The study was undertaken at the Source Area BioREmediation (SABRE) research site in the UK, which is the focus of a major four-year international research programme investigating the in-situ enhance bioremediation of a dense non-aqueous phase liquid (DNAPL) chlorinated solvent source zone. The site is characterised by a shallow superficial sand and gravel aquifer underlain by a low permeability mudstone. A trichloroethene (TCE) source zone, associated with a former manufacturing facility, is distributed across much of the research site. The principal objectives of this phase of the study were to identify the geology, and lithological variability, across the site; and to delineate the contaminant source distribution.

The GSI3D (Geological Surveying and Investigation in 3 Dimensions; © INSIGHT Geologische Softwaresysteme GmbH) modelling package was used to reconstruct and visualise the site geology and integrate contaminant data on a point basis. The result of the study revealed a complex geological setting with the distribution of DNAPL largely controlled by the architecture of the contact between the gravels sequence and the underlying mudstones. The contaminant distribution was also controlled by subtle changes in grain size and permeability within litho-stratigraphic units. Uncertainty analysis of the 3D geological model gave a measure of our confidence in the model and identified where further site investigation was required to reduce uncertainty.

The method used for detailed 3D reconstruction and visualisation of the site data is presented and a method to assess the uncertainty of 3D geological models described. Recommendations for future applications and developments are also discussed.