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Equipping for risk: Lessons learnt from the UK shale-gas experience on assessing environmental risks for the future geoenergy use of the deep subsurface

Lookup NU author(s): Dr Jean Hall, Professor David ManningORCiD



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


© 2024 The Authors. Summary findings are presented from an investigation to improve understanding of the environmental risks associated with developing an unconventional-hydrocarbons industry in the UK. The EQUIPT4RISK project, funded by UK Research Councils, focused on investigations around Preston New Road (PNR), Fylde, Lancashire, and Kirby Misperton Site A (KMA), North Yorkshire, where operator licences to explore for shale gas by hydraulic fracturing (HF) were issued in 2016, although exploration only took place at PNR. EQUIPT4RISK considered atmospheric (greenhouse gases, air quality), water (groundwater quality) and solid-earth (seismicity) compartments to characterise and model local conditions and environmental responses to HF activities. Risk assessment was based on the source-pathway-receptor approach. Baseline monitoring of air around the two sites characterised the variability with meteorological conditions, and isotopic signatures were able to discriminate biogenic methane (cattle) from thermogenic (natural-gas) sources. Monitoring of a post-HF nitrogen-lift (well-cleaning) operation at PNR detected the release of atmospheric emissions of methane (4.2 ± 1.4 t CH4). Groundwater monitoring around KMA identified high baseline methane concentrations and detected ethane and propane at some locations. Dissolved methane was inferred from stable-isotopic evidence as overwhelmingly of biogenic origin. Groundwater-quality monitoring around PNR found no evidence of HF-induced impacts. Two approaches for modelling induced seismicity and associated seismic risk were developed using observations of seismicity and operational parameters from PNR in 2018 and 2019. Novel methodologies developed for monitoring include use of machine learning to identify fugitive atmospheric methane, Bayesian statistics to assess changes to groundwater quality, a seismicity forecasting model seeded by the HF-fluid injection rate and high-resolution monitoring of soil-gas methane. The project developed a risk-assessment framework, aligned with ISO 31000 risk-management principles, to assess the theoretical combined and cumulative environmental risks from operations over time. This demonstrated the spatial and temporal evolution of risk profiles: seismic and atmospheric impacts from the shale-gas operations are modelled to be localised and short-lived, while risk to groundwater quality is longer-term.

Publication metadata

Author(s): Smedley PL, Allen G, Baptie BJ, Fraser-Harris AP, Ward RS, Chambers RM, Gilfillan SMV, Hall JA, Hughes AG, Manning DAC, McDermott CI, Nagheli S, Shaw JT, Werner MJ, Worrall F

Publication type: Article

Publication status: Published

Journal: Science of the Total Environment

Year: 2024

Volume: 921

Print publication date: 15/04/2024

Online publication date: 17/02/2024

Acceptance date: 15/02/2024

Date deposited: 11/03/2024

ISSN (print): 0048-9697

ISSN (electronic): 1879-1026

Publisher: Elsevier BV


DOI: 10.1016/j.scitotenv.2024.171036

PubMed id: 38373449


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Funder referenceFunder name
NE/R017913/1Natural Environment Research Council (NERC)