The subsurface of the UK has long been used as a source of resources for energy, minerals wealth, water and waste disposal. In the UK’s ever more crowded cities an ever greater proportion of the basic infrastructure such as cables, pipes, transport routes, pumping stations and electrical substations are being buried to free up valuable surface area for housing, industry and green spaces.
Geological maps and models have been developed as a way of expressing the complexity of the subsurface. Understanding the richness of information that these models contain requires the involvement of a geologist to translate this information.
Information about the subsurface of the UK is not just needed by geologists but also people such as planners, architects and engineers who need to understand the likely subsurface conditions but have no geological training. These users do not understand the complex descriptions of the geology that professional geologists use but they do require numerical subsurface properties to support their work.
Increasingly, scientists are requiring numeric values that describe the properties of different geology to understand, for example, how porosity affects the flow of fluid through a particular unit. Maps imply that the geology of the United Kingdom is well understood and neatly categorised by mapped units (e.g. formations, members, beds) but this is at best a simplification of the real variability of the subsurface geology. Whilst some units are defined by a single lithology, others are defined by combinations of lithologies which may vary in their proportions. Others vary by location depending upon where they were deposited in the basin. In addition these units may have been subject to very different processes since their deposition. Therefore the properties of these units may vary significantly with location.
The BGS Parameterisation and Statistics team are trying to understand this heterogeneity and to express it numerically. Simplistic single average property values are no longer sufficient. Therefore the physical properties of the subsurface need to be analysed statistically to understand its variability. Digital geological models can then be used to serve this to end users.
Key outputs for the team include:
Contact Andy Kingdon for further information