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Section Contents
Current Research
Project Details
MSc by Research Project Area: "Active and Passive Seismic Interferometry in Directionally Biased Wavefields"
Principal Supervisor: Prof. Andrew Curtis
Secondary Supervisor: Prof. Xiang Yang Li
(British Geological Survey)
Industry Supervisor: Dr David Halliday
(Schlumberger Cambridge Research)
Project Background
‘Seismic Interferometry’ is a relatively new technique which – through theoretical analysis and practical application to date – promises to increase the flexibility of both exploration and earthquake seismology.
Two broad categories can be defined: ‘Passive seismic interferometry’ is a term commonly used to describe the process of retrieving coherent seismic data from ambient seismic noise through the application of one of a suit of mathematical operations, most-commonly cross-correlation. Further to this, ‘Active source seismic interferometry’ refers to a very similar approach applied to seismic recordings reliant upon active sources of energy, for example explosive sources as used in conventional exploration seismology.
A number of shortcomings of the interferometric process arise on application to real life acquired data sets. These shortcomings reduce the method's ability to accurately recover data comparable to conventional active source data. One principal requirement (for conventional cross-correlation interferometry) which is rarely fulfilled is that of an even distribution of active or passive seismic sources from all directions (a uniform and complete source distribution). Failing to comply with this requirement can lead to significant errors in the interferometric estimates recovered. The main topic of my research project is to investigate methods by which interferometric estimates can be corrected to account for directional bias in the noise source distribution (non-uniform directionaly) used to create these estimates. This work is an important step in increasing the applicability of seismic interferometry in both global and exploration seismology.
The research is carried out in collaboration with Schlumberger Cambridge Research and funded via the NERC CASE studentship initiative.
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