Use of electrical resistivity tomography to detect temporal near surface changes providing reliable uncertainty estimates for pollution risk assessment

This postdoctoral project supervised by Prof Andrew Curtis and Dr Mark Chapman undertaken by PDRA Erica Galetti initially had the goals of analysing microseismicity distributions from actual fracking data their correlations with productionrelated activity and the extent to which anisotropy could be detectable in order to assess fracture orientations A data set for this was in the universitys possession in Edinburgh at the time of writing the proposal Unfortunately by the time the PDRA was recruited the data were not available for this purpose the industrial owner of the data restricted their use As a result it was necessary to redesign the project for this PDRARemaining in the same general area of using Geophysics to detect subsurface information related to risk assessment of fracking operations the following project was thought an appropriate replacement during such operations the nearsubsurface depths of tens to lowhundreds of metres is potentially at risk of pollution from escaping drilling fluids reservoir fluids migrating up fracture networks and by the escape of pollutants from the drilling and production platform or injectionwater pool To enable the nearsubsurface to be monitored and concomitant pollution risks tracked over time a new subsurface monitoring method is being developed and tested that uses electrical resistivity tomography ERT to image the near surface The key new feature of the method is that it is a fully nonlinear Monte Carlo method which for the first time produces reliable estimates of ERT uncertainty in subsurface properties Reliable uncertainty estimates are necessary for pollution risk assessment but todate they have been unavailable Hence this new project direction makes a significant contribution to risk assessment of fracking operations