Method for extracting angle-domain common image gathers in Kirchhoff beam migration

Kirchhoff beam migration is a simplified Gaussian beam migration,which omits the dynamic information and can calculate multi-arrival traveltime,so it is a high-precision and fast seismic imaging method.In the imaging process,extracting common image gathers can be used for velocity analysis,improving the accuracy of modeling and imaging quality.Compared with the conventional common image gathers extracting methods,the angle-domain common image gathers extracting method can avoid the artifacts caused by multi-arrival seismic waves.The authors present a new method of extracting common image gathers in angle-domain from Kirchhoff beam migration and verify the method by numerical calculations.

Tomographic velocity inversion for ADCIGs in areas with a rugged surface

Pre-stack depth migration velocity analysis is one of the key techniques influencing image quality. As for areas with a rugged surface and complex subsurface, conventional prestack depth migration velocity analysis corrects the rugged surface to a known datum or designed surface velocity model on which to perform migration and update the velocity. We propose a rugged surface tomographic velocity inversion method based on angle-domain common image gathers by which the velocity field can be updated directly from the rugged surface without static correction for pre-stack data and improve inversion precision and efficiency. First, we introduce a method to acquire angle-domain common image gathers （ADCIGs） in rugged surface areas and then perform rugged surface tornographic velocity inversion. Tests with model and field data prove the method to be correct and effective.

Extraction of amplitude-preserving angle gathers based on vector wavefield reverse-time migration

Angle-domain common-image gathers （ADCIGs） transformed from the shot- domain common-offset gathers are input to migration velocity analysis （MVA） and prestack inversion. ADCIGs are non-illusion prestack inversion gathers, and thus, accurate. We studied the extraction of elastic-wave ADCIGs based on amplitude-preserving elastic-wave reverse- time migration for calculating the incidence angle of P- and S-waves at each image point and for different source locations. The P- and S-waves share the same incident angle, namely the incident angle of the source P-waves. The angle of incidence of the source P-wavefield was the difference between the source P-wave propagation angle and the reflector dips. The propagation angle of the source P-waves was obtained from the polarization vector of the decomposed P-waves. The reflectors＇ normal direction angle was obtained using the complex wavenumber of the stacked reverse-time migration （RTM） images. The ADCIGs of P- and S-waves were obtained by rearranging the common-shot migration gathers based on the incident angle. We used a horizontally layered model, the graben medium model, and part of the Marmousi-II elastic model and field data to test the proposed algorithm. The results suggested that the proposed method can efficiently extract the P- and S-wave ADCIGs of the elastic-wave reverse-time migration, the P- and S-wave incident angle, and the angle-gather amplitude fidelity, and improve the MVA and prestack inversion.

Numerical simulation of scattering wave imaging in a goaf

Goafs are threats to safe mining.Their imaging effects or those of other complex geological bodies are often poor in conventional reflected wave images.Hence,accurate detection of goafs has become an important problem,to be solved with a sense of urgency.Based on scattering theory,we used an equivalent offset method to extract Common Scattering Point gathers,in order to analyze different scattering wave characteristics between Common Scattering Point and Common Mid Point gathers and to compare stack and migration imaging effects.Our research results show that the scattering wave imaging method is more efficient than the conventional imaging method and is therefore a more effective imaging method for detecting goafs and other complex geological bodies.It has important implications for safe mining procedures and infrastructures.

A Quadratic precision generalized nonlinear global optimization migration velocity inversion method

An important research topic for prospecting seismology is to provide a fast accurate velocity model from pre-stack depth migration. Aiming at such a problem, we propose a quadratic precision generalized nonlinear global optimization migration velocity inversion. First we discard the assumption that there is a linear relationship between residual depth and residual velocity and propose a velocity model correction equation with quadratic precision which enables the velocity model from each iteration to approach the real model as quickly as possible. Second, we use a generalized nonlinear inversion to get the global optimal velocity perturbation model to all traces. This method can expedite the convergence speed and also can decrease the probability of falling into a local minimum during inversion. The synthetic data and Mamlousi data examples show that our method has a higher precision and needs only a few iterations and consequently enhances the practicability and accuracy of migration velocity analysis （MVA） in complex areas.

Multiscale Stategies in Automatic Image-Domain Waveform Tomography

Multiscale strategies are very important in the successful application of waveform-based velocity inversion. The strategy that sequentially preceeds from long to short scale of velocity model, has been well developed in full waveform inversion （FWI） to solve the local mininum problem. In contrast, it＇s not well understood in the image-domain waveform tomography （IWT）, which back-projects incoherent waveform components of the common image gather into velocity updates. IWT is less prone to local minimum problem but tends to build long-scale model with low resolution. In order to build both long- and short-scale model by IWT, we discuss several multiscale strategies restricted in the image domain. The strategies include model reparameterization, objective function switching and gradient rescaling. Numerical tests on Marmsousi model and real data demonstrate that our proposed multiscale IWT is effective in buidling velocity model with wide wavenumber spectrum.