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An inverse scattering series method for attenuating elastic multiples from multicomponent land and ocean bottom seismic data

University of British Columbia

A method exists for marine seismic data which removes all orders of free surface multiples and suppresses all orders of internal multiples while leaving primaries intact. This method is based on the inverse scattering series and makes no assumptions about the subsurface earth model. The marine algorithm assumes that the sources and receivers are located in the water column. In the context of land and ocean bottom data, the sources and receivers are located on or in an elastic medium. This opens up the possibility of recording multicomponent seismic data. Because both compressional (P) and shear (S) primaries are recorded in multicomponent data, it has the potential for providing a more complete picture of the subsurface. Coupled with the benefits of the P and S primaries are a complex set of elastic free surface and internal multiples. In this thesis, I develop an inverse scattering series method to attenuate these elastic multiples from multicomponent land and ocean bottom data. For land data, this method removes elastic free surface multiples. For ocean bottom data, multiples associated with the top and bottom of the water column are removed. Internal multiples are strongly attenuated for both data types. In common with the marine formulation, this method makes no assumptions about the earth below the sources and receivers, and does not affect primaries. The latter property is important for amplitude variation with offset analysis (AVO). The theory for multiple attentuation requires four component (two source, two receiver) data, a known near surface or water bottom, near offsets, and a known source wavelet. Tests on synthetic data indicate that this method is still effective using data with less than four components and is robust with respect to errors in estimating the near surface or ocean bottom properties.

Thesis/Dissertation

application/pdf

2009-03-31

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http://hdl.handle.net/2429/6665

Environmental Sciences

University of British Columbia

UBCV

DSpace