Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.598649
Title: Coalescence microseismic mapping : an imaging method for the detection and location of seismic events
Author: Drew, J.
Awarding Body: University of Cambridge
Current Institution: University of Cambridge
Date of Award: 2010
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Abstract:
The Coalescence Microseismic Mapping method I have developed is applicable to event detection and location for a sparse array, while still benefiting from rigorous statistical analysis by averaging data over the array. Formulated within a Bayesian framework with respect to traveltime, the automated method simultaneously identifies and quantitatively images source location, by mapping a scalar signal that characterizes both the presence and timing of a seismic arrival. Unlike traveltime inversion, the numerical approach is not restrictive in regards to the type and distribution of errors. Effectively providing the probability density functions, the approach also allows for new ways to aggregate, visualize and interpret the results. Signal phase information can be assimilated in the solution when this can be recovered from the data, with the potential for improving location resolution. The method can be incorporated within a general integrated workflow, including an iterative or global inversion for multiple parameters. The theory is discussed in detail then applied to two datasets. The first is the integrated analysis of data acquired by a surface array deployed in the vicinity of Askja Volcano, Iceland. Here the signal phase information is recovered after correction for shear wave splitting and compensation for attenuation and station response. The second is for data acquired by a sub-surface array, monitoring seismic activity associated with hydraulic fracturing of a hydrocarbon reservoir. In this example the location is further constrained by including weighted signal polarization information in the search.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.598649  DOI: Not available
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