Study On Surface-Related Multiple Attenuation In Donghai Area

In seismic prospecting especially on the sea, it is the multiple wave that causes the SNR of seismic data to reduce greatly, disturbs the identifiability of primary reflection, brings enormous difficulty on velocity analysis and excursion before and after stacking, and then affects the seismic imaging authenticity and reliability, sometimes may be false. Multiple may seriously influence seismic interpretation work also. So it is very important and necessary for multiple suppression. The research of this dissertation is funded by the Hi-tech research and development program of China (Grant No. 2006AA09Z339).Since the 20th century 50's, a lot of multiple suppressing methods have come out, which make use of different characteristics of multiple. methods that suppress multiples can be classified into two broad categories: One is based on the moveout between primary and multiples. Typical methods of the first class consist of predictive deconvolution, normal moveout stacking, f-k transformation, Tau-p transformation, parabola Radon transformation and beamforming. They can be called as seismography method based on the geometry. The second one is mainly based on wave equation, which predict, match it with the original data and then subtract multiples from the input data. The wave equation methods include Wavefield Extrapolated method, Iterative Feedback method and Inverse Scattering Series method. In this dissertation, a comprehensive study has been done on the wave equation-based methods.From the perspective of the acoustic wave equation theory, using the Kirchhoff Integral solution, we obtained the wave field extrapolation formula in the frequency-space domain. Regardless of surface reflection, the primary propagates downward, reflects at the subsurface reflector, and then propagates back. Taking the interface of seawater-to-air into account, the so-called surface-related multiple has been modeled. The surface-related multiple elimination can be treated as an inverse procedure of surface-related multiple modeling. Algorithms, formulas, program flowcharts for the surface-related multiple have been given in detail in this dissertation.A surface-related multiple-elimination method can be formulated as an iterative procedure: the output of one iteration step is used as input for the next iteration step. In this paper it is shown that the procedure can be made very efficient if a good initial estimate of the multiple-free data set can be provided in the first iteration, and in many situations, the synthetic method may provide such an estimate. It is also shown that for each iteration, the inverse source wavelet can be accurately estimated by a nonlinear (Huber norm) inversion process. The iterative multiple elimination process, together with the source wavelet estimation, are illustrated with numerical experiments as well as with field data examples. The results show that the surface related multiple-elimination process is very effective in time gates where the moveout properties of primaries and multiples are very similar.From the physical insight, surface multiple attenuation is to combining primary events to predict a multiple is similar to the diffraction-aperture problem of classical optics. Although the algorithm requires no assumptions or modeling regarding the positions and reflection coefficients of the multiple-causing reflectors, it does require complete internal physical consistency from the optical veiwpoint. SRMA also has several weaknesses. The wavelet in the data contaminates the multiple prediction operator and has to be removed in order to predict multiples accurately. Since the prediction operator is the data, it is only sampled for locations where shots were initiated, not in general the same as the locations were traces were recorded. The SRMA operator tends to overpredict higherorder multiples because it should be convolving with an operator containing only subsurface primaries and interbeds. As a result it must resort to some type of iterative scheme to drive this contamination down. To sidestep acquisition limitations, source wavelet contamination and overprediction of higher order multiples, we have developed a method which essentially models surface-related multiples by adding a synthetic shot to the data. More specifically, each input trace is convolved with a synthetically-generated shot record consisting of one or more key subsurface primary reflections. These records are impulse response of the beneath, which are generated by the so-called reflectivity method. The resulting operators have several appealing features. They are clean operators, having no source wavelet contamination and little or no aliasing. By construction they are available for any source-receiver combination desired. By modeling only primaries into the operator, we avoid the geometric overprediction of higherorder multiples that plagues SRMA. Because l 1norm adaptive filter is incorporated, we retain much of the ability of SRMA to honor lateral amplitude variations induced by these reflectors in the predicted multiples.The synthetic and real examples clearly justify the validity of the technology presented in this dissertation.