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Research interests
My research interests are utilising deep learning methods (e.g. Convolutional Neural Networks) to detect phase arrivals of hydraulic fracturing induced seismicity. I work on a continuous dataset containing >38,000 events from the Preston New Road shale gas site. I am particularly interested in the spatio-temporal relationships (e.g. earthquake clustering) that the machine-learning enhanced event catalogues may reveal.
Publications
Recent publications
01/01/2025Deep learning phase pickers: how well can existing models detect hydraulic-fracturing induced microseismicity from a borehole array?
Geophysical Journal International
Impacts of Deep Learning to Detect Induced Seismicity: a Case Study from Preston New Road, UK
85th EAGE Annual Conference & Exhibition
Repurposing Legacy Boreholes for Microseismic Monitoring
Thesis
Using deep learning for phase detection and event location on hydraulic fracturing-induced seismicity
Supervisors
Award date
21/01/2021