Enhancing the information content of geophysical data for nuclear site characterisation by Chak-Hau Michael Tso B.S. M.S. Supervisor: Prof. Andrew Binley Thesis submitted in partial fulfilment for the degree of Doctor of Philosophy in Environmental Science September 2019 Lancaster Environment Centre Abstract Enhancing the information of geophysical data for nuclear site characterisation Chak-Hau Michael Tso A thesis submitted for the degree of Doctor of Philosophy, Lancaster University September 2019 Abstract Our knowledge and understanding to the heterogeneous structure and processes occurring in the Earth’s subsurface is limited and uncertain. The above is true even for the upper 100m of the subsurface, yet many processes occur within it (e.g. migration of solutes, landslides, crop water uptake, etc.) are important to human activities. Geophysical methods such as electrical resistivity tomography (ERT) greatly improve our ability to observe the subsurface due to their higher sampling frequency (especially with autonomous time-lapse systems), larger spatial coverage and less invasive operation, in addition to being more cost-effective than traditional point- based sampling. However, the process of using geophysical data for inference is prone to uncertainty. There is a need to better understand the uncertainties embedded in geophysical data and how they translate themselves when they are subsequently used, for example, for hydrological or site management interpretations and decisions. This understanding is critical to maximize the extraction of information in geophysical data. To this end, in this thesis, I examine various aspects of uncertainty in ERT and develop new methods to better use geophysical data quantitatively. The core of the thesis is based on two literature reviews and three papers. In the first review, I provide a comprehensive overview of the use of geophysical data for nuclear site characterization, especially in the context of site clean- up and leak detection. In the second review, I survey the various sources of uncertainties in ERT studies and the existing work to better quantify or reduce them. I propose that the various steps in the general workflow of an ERT study can be viewed as a pipeline for information and uncertainty propagation and suggested some areas have been understudied. One of these areas is measurement errors. In paper 1, I compare various methods to estimate and model ERT measurement errors using two i Abstract long-term ERT monitoring datasets. I also develop a new error model that considers the fact that each electrode is used to make multiple measurements. In paper 2, I discuss the development and implementation of a new method for geoelectrical leak detection. While existing methods rely on obtaining resistivity images through inversion of ERT data first, the approach described here estimates leak parameters directly from raw ERT data. This is achieved by constructing hydrological models from prior site information and couple it with an ERT forward model, and then update the leak (and other hydrological) parameters through data assimilation. The approach shows promising results and is applied to data from a controlled injection experiment in Yorkshire, UK. The approach complements ERT imaging and provides a new way to utilize ERT data to inform site characterisation. In addition to leak detection, ERT is also commonly used for monitoring soil moisture in the vadose zone, and increasingly so in a quantitative manner. Though both the petrophysical relationships (i.e., choices of appropriate model and parameterization) and the derived moisture content are known to be subject to uncertainty, they are commonly treated as exact and error‐free. In paper 3, I examine the impact of uncertain petrophysical relationships on the moisture content estimates derived from electrical geophysics. Data from a collection of core samples show that the variability in such relationships can be large, and they in turn can lead to high uncertainty in moisture content estimates, and they appear to be the dominating source of uncertainty in many cases. In the closing chapters, I discuss and synthesize the findings in the thesis within the larger context of enhancing the information content of geophysical data, and provide an outlook on further research in this topic. ii Executive summary for the nuclear industry Executive summary for the nuclear industry Uncertainty in the subsurface characterisation of nuclear sites poses significant risks in terms of operational cost and environmental protection. Improved knowledge of the uncertainty of subsurface properties and processes is needed in order to enhance risk mitigation. Geophysical methods, such as electrical resistivity tomography (ERT), provide a cost-effective way to delineate variations in subsurface properties and monitor subsurface processes, however, the uncertainty in the results from such methods is often overlooked. A recent successful time-lapse ERT field trial conducted at Sellafield's Magnox Swarf Storage Silo (MSSS) highlights the potential of these methods [1] by showing 3D resistivity variations over time due to saline tracer injection. This PhD project explores various ways to better exploit information from ERT and to track the associated uncertainty in subsurface characterisation. This includes better understanding of the ERT data, and incorporating ancillary data sources to the ERT analysis. We have studied the error structure in ERT data and proposed a new error model for geophysical measurements, which shows improved ERT inversion results and uncertainty estimation [2]. Recently, we have shown that there exists large variability in field petrophysical relationships and have developed a workflow quantifying pore water states (e.g. soil water content) derived from ERT. Even though different petrophysical relationships give consistent estimates of the change in total moisture, the estimates have large uncertainty bounds [3]. Our study also illustrates the joint use of coupled hydrogeophysical modelling and data assimilation to effectively estimate flow and transport properties in leak plumes. Our method proposes a range of hydrological models and then constrains them with time-lapse ERT data through data assimilation. The advantages of this method includes the flexibility to incorporate prior hydrogeological information and the ability to estimate flow and leak parameters of interest directly. The ensemble of hydrological model estimates also readily provides useful metrics for site management decisions, e.g. mass flux and mass discharge at any location or area within the model domain. iii Executive summary for the nuclear industry We have applied the above methods to the data collected from the Sellafield field trial and other sites. Overall, our work addresses the needs of the Nuclear Decommissioning Authority (NDA) by offering a suite of methods that can make geophysical methods more reliable and informative for site characterisation. Systematic application of ERT at NDA sites should contribute to a reduction in costs and risks in managing NDA's contaminated land portfolio. References: [1] Kuras et al. (2016) Science of the Total Environment. DOI: 10.1016/j.scitotenv.2016.04.212 [2] Tso et al. (2017) Journal of Applied Geophysics. DOI: 10.1016/j.jappgeo.2017.09.009 [3] Tso et al. (2019) Water Resources Research. DOI: 10.1029/2019WR024964 iv Table of Contents Table of Contents Contents Abstract ...................................................................................................................................... i Executive summary for the nuclear industry ..................................................................... iii Table of Contents .................................................................................................................... v Acknowledgment ................................................................................................................... vi Declaration ............................................................................................................................ viii List of Figures ......................................................................................................................... ix List of Tables ......................................................................................................................... xvi List of Acronyms ................................................................................................................. xvii 1. Introduction ................................................................................................................... 18 1.1 Background ............................................................................................................ 18 1.2 Objectives and aims .............................................................................................. 18 1.3 Outline .................................................................................................................... 20 2. Geophysical methods for nuclear site characterisation ........................................... 23 3. Sources of uncertainties in electrical resistivity tomography (ERT): a review ..... 59 4. Paper 1: Improved characterisation and modelling of measurement errors in electrical resistivity tomography (ERT) surveys ............................................................. 115 5. Paper 2: Integrated hydrogeophysical modelling and data assimilation for geoelectrical