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Title: Microseismic and geomechanical investigation of injection-induced fault reactivation
Author: Kettlety, Tom
ISNI:       0000 0005 0294 1450
Awarding Body: University of Bristol
Current Institution: University of Bristol
Date of Award: 2020
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Earthquakes caused by human activities are of increasing concern around the world. Geothermal energy, waste water disposal, carbon dioxide sequestration, and hydraulic fracturing, or fracking, have all been associated with seismicity of varying severity, and over the past decade the number of cases has noticeably increased. Understanding the controls of induced seismicity is now an integral component of one of the future's biggest challenges: meeting energy demand whilst simultaneously reducing emissions. In this thesis I use measurements of microseismic events (broadly M < 2) to examine the physical processes controlling the activation of faults, and test statistical methods to forecast the onset of larger earthquakes. I examine multiple case studies of hydraulic fracturing-induced seismicity, using microseismic data from operations in the Horn River Basin, British Columbia, Canada, and at the Preston New Road hydraulic fracturing site near Blackpool, Lancashire, UK. Using these data, I show that one of the mechanisms that strongly controls the likelihood and behaviour of fault activation by injection is the in situ stress state. In chapters 2 and 5, microseismic data and geomechanical modelling are used to show that the slip tendency of activated faults can affect not only the mechanisms controlling fault activation, but also the magnitudes of induced events for a given pressure perturbation. In chapter 2, I show that smaller magnitude stress changes associated with elastic deformation of microseismic events are not a significant driver in activating faults in areas of low stress anisotropy, where slip tendency is low. In chapter 3, I show that elastic stress transfer from the opening of hydraulic fractures appeared to be controlling which parts of a fault were most active once it was stimulated by injection. In chapter 4, I show that statistics-based maximum magnitude forecasting can be used to forecast induced seismicity in real-time.
Supervisor: Kendall, John Michael ; Verdon, James Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available