Dr Cindy Lim
BSc, MSc, PhD
Expertise
An observational seismologist using passive seismology, machine learning applications and beamforming on large-N seismic arrays and DAS datasets to detect and characterise fluid-induced seismicity.
Current positions
Senior Research Associate
School of Earth Sciences
Contact
Press and media
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Research interests
My research interests are in using a combination of passive seismology, machine learning applications and beamforming on large continuous datasets recorded by large-N seismic arrays and DAS to detect and characterise fluid-induced seismicity. I am particularly interested in the spatio-temporal relationships (e.g. earthquake clustering) and structural insights that machine-learning enhanced event catalogues can reveal.
Publications
Recent publications
28/10/2025Deep Learning-Enhanced Catalogue of Induced Microseismicity at Preston New Road-1z, UK
Deep 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
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
