Positioning of grid points in wave front construction

In view of the relative positioning problem between non-regular quadrilateral grids and regular rectangle grid nodes in the wave front construction method, concrete realization problems with four grid positioning methods （vector cross product judgment, angle sum, intersection-point, and signs comparison algorithms） in wave front construction which are commonly used in computer graphics are compared and analyzed in this paper. Based on the stability analysis of the location method, the calculation examples show that the vector cross product judgment method is faster and more accurate than other methods in the realization of the relative positioning between non-regular quadrilateral grids and regular rectangle grid nodes in wave front construction. It provides precise grid point attribute values for the next steps of migration and demigration.

A stabilized least-squares imaging condition with structure constraints

Conventional shot-gather migration uses a cross-correlation imaging condition proposed by Clarebout （1971）, which cannot preserve imaging amplitudes. The deconvolution imaging condition can improve the imaging amplitude and compensate for illumination. However, the deconvolution imaging condition introduces instability issues. The least-squares imaging condition first computes the sum of the cross-correlation of the forward and backward wavefields over all frequencies and sources, and then divides the result by the total energy of the forward wavefield. Therefore, the least-squares imaging condition is more stable than the classic imaging condition. However, the least-squares imaging condition cannot provide accurate results in areas where the illumination is very poor and unbalanced. To stabilize the least-squares imaging condition and balance the imaging amplitude, we propose a novel imaging condition with structure constraints that is based on the least-squares imaging condition. Our novel imaging condition uses a plane wave construction that constrains the imaging result to be smooth along geological structure boundaries in the inversion frame. The proposed imaging condition improves the stability of the imaging condition and balances the imaging amplitude. The proposed condition is applied to two examples, the horizontal layered model and the Sigsbee 2A model. These tests show that, in comparison to the damped least-squares imaging condition, the stabilized least-squares imaging condition with structure constraints improves illumination stability and balance, makes events more consecutive, adjusts the amplitude of the depth layers where the illumination is poor and unbalanced, suppresses imaging artifacts, and is conducive to amplitude preserving imaging of deep layers.