Earth Science and Engineering, Imperial College London
Doi
Abstract
Reflection seismology is widely used to map the subsurface geological structure of
the Earth. Seismic multiples can contaminate seismic data and are therefore due to be
removed. For seismic multiple attenuation, wave-equation based methods are proved
to be effective in most cases, which involve two aspects: multiple prediction and
multiple subtraction. Targets of both aspects are to develop and apply a fully datadriven
algorithm for multiple prediction, and a robust technique for multiple
subtraction. Based on many schemes developed by others regarding to the targets, this
thesis addresses and tackles the problems of wave-equation based seismic multiple
attenuation by several approaches.
First, the issue of multiple attenuation in land seismic data is discussed. Multiple
Prediction through Inversion (MPTI) method is expanded to be applied in the poststack
domain and in the CMP domain to handle the land data with low S/N ratio,
irregular geometry and missing traces. A running smooth filter and an adaptive
threshold K-NN (nearest neighbours) filter are proposed to help to employ MPTI on
land data in the shot domain.
Secondly, the result of multiple attenuation depends much upon the effectiveness
of the adaptive subtraction. The expanded multi-channel matching (EMCM) filter is
proved to be effective. In this thesis, several strategies are discussed to improve the
result of EMCM. Among them, to model and subtract the multiples according to their
orders is proved to be practical in enhancing the effect of EMCM, and a masking filter
is adopted to preserve the energy of primaries. Moreover, an iterative application of
EMCM is proposed to give the optimized result.
Thirdly, with the limitation of current 3D seismic acquisition geometries, the
sampling in the crossline direction is sparse. This seriously affects the application of
the 3D multiple attenuation. To tackle the problem, a new approach which applies a
trajectory stacking Radon transform along with the energy spectrum is proposed in
this thesis. It can replace the time-consuming time-domain sparse inversion with
similar effectiveness and much higher efficiency.
Parallel computing is discussed in the thesis so as to enhance the efficiency of
the strategies. The Message-Passing Interface (MPI) environment is implemented in
most of the algorithms mentioned above and greatly improves the efficiency
