Benefits of Cross-Correlation Analysis for Monitoring Underground Gas Storage Operations Using EGMS data: A Case Study of Hatfield Moors (UK)

The aim of the study is to analyse the ground displacement behaviour observed above an Underground Gas Storage (UGS) site located at Hatfield Moors (United Kingdom), with a focus on understanding its implications for decarbonisation efforts. Hatfield is a larger wetland system in England, located in South Yorkshire. The UGS reservoir is located below an extensive peatland and serves as an active onshore analogue for a Carbon Capture and Storage (CCS) site used by the British Geological Survey (BGS) as part of the SENSE (assuring integrity of CO₂ storage sites through ground surface monitoring) project. The investigation uses satellite Interferometric Synthetic Aperture Radar (InSAR) data from the European Ground Motion Service (EGMS) to assess the environmental impact of UGS operations, leveraging the need for continuous and real-time monitoring of ground movements induced by gas storage activities. The utilisation of freely available, open-source and user-friendly Sentinel-1 data facilitates the analysis of ground motion patterns over Hatfield Moors, thereby highlighting displacements ranging from -5.0 to -10.0 mm/year within the peat bog. Furthermore, the Time Series (TS) of vertical ground displacement from January 2018 to December 2022 reveals a seasonality in ground motion, with uplift observed in late winter and subsidence in late summer, with a periodicity of approximately 1 year and a magnitude of ±10.0 mm. The study emphasises the need to investigate the underlying causes of ground fluctuations at gas storage sites through in-depth analysis. The results highlight the versatility of InSAR in integrating with a range of monitoring tools and methodologies, thereby facilitating multidisciplinary and holistic analyses. Cross-correlation analyses further elucidate temporal relationships between different datasets, evaluating InSAR TS, UGS injection/withdrawal data and piezometric data. This involves decomposing the TS into distinct components, including trend, seasonality and residuals. The case of Hatfield Moore shows a significant discrepancy between the UGS data and the InSAR TS, while it demonstrates a clear correlation between the groundwater data and the InSAR TS. By integrating insights from geology, hydrology and remote sensing technologies, the study navigates the complexities inherent in areas of overlapping phenomena. The work demonstrates the huge important of free available data and how much they that accurate interpretation is fundamental for informed decision-making, particularly at sites such as Hatfield Moors, where the convergence of peat activities and storage operations highlights the need for interdisciplinary analysis to understand the underlying causes of ground fluctuation.