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.
- Machine Learning
- statistical modelling
- induced seismicity
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Using deep learning for phase detection and event location on hydraulic fracturing-induced seismicityAuthor: Lim Shin Yee, C., 21 Jan 2021
Supervisor: Werner, M. (Supervisor)
Student thesis: Master's Thesis › Master of Science (MSc)File