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In this paper, we analyze the absorption effect of the hybrid absorbing boundary condition (ABC) with various hybrid modes, and propose a cosine-type optimized weighted hybrid mode taking into account the boundary reflection intensity of the inner and outer boundaries of transition area. Additionally, we derive a new finite-difference scheme of the second-order Higdon ABC and the corner equation for Graphic Processing Unit (GPU) acceleration. On this basis, a new type of second-order Higdon hybrid ABC applicable for GPU acceleration is established in the acoustic finite-difference modeling. Numerical experiments demonstrate that the proposed cosine-type weighted hybrid mode can achieve a better absorption effect compared with other weighted hybrid modes; the second-order Higdon ABC based on the proposed new finite-difference scheme can effectively improve the GPU speed-up ratio and is more effective in large-scale wavefield high-precision simulation based on GPU acceleration.

This paper introduces an internal multiple prediction method based on imaging profile prediction and Kirchhoff demigration. First, based on an inputted prestack time migration profile, the method predicts the prestack time migration profile that only includes internal multiples by inverse scattering series method. Second, the method uses velocity-weighted Kirchhoff demigration to create shot gathers that contains only internal multiples. Internal multiple prediction based on the prestack time migration profile effectively reduces the computational cost of multiple predictions, and the internal-multiple shot gathers created by Kirchhoff demigration remarkably reduces the complexity of the practical problem. Internal multiple elimination can be conducted through the combined adaptive multiple subtraction based on event tracing. Synthetic and field data tests show that the method effectively predicts internal multiples and possesses considerable potential in field data processing, particularly in areas where internal multiples develop seriously.

The gradient preconditioning approach based on seismic wave energy can effectively avoid the huge memory consumption of the gradient preconditioning algorithms based on the Hessian matrix. However, the accuracy of this approach is prone to be influenced by the energy of reflected waves. To tackle this problem, the paper proposes a new gradient preconditioning method based on the energy of transmitted waves. The approach scales the gradient through a precondition factor, which is calculated by the ‘approximate transmission wavefield’ simulation based on the nonreflecting acoustic wave equation. The method requires no computing nor storing of the Hessian matrix and its inverse matrix. Furthermore, the proposed method can effectively eliminate the effects of geometric spreading and disproportionality in the gradient illumination. The results of model experiments show that the time-domain full waveform inversion (FWI) using the gradient preconditioning based on transmitted wave energy can achieve higher inversion accuracy for deep high-velocity bodies and their underlying strata in comparison with the one using the gradient preconditioning based on seismic wave energy. The field marine seismic data test shows that our proposed method is also highly applicable to the FWI of field marine seismic data.

In a typical sandy bottom area of the South Yellow Sea, measurement of acoustic bottom backscattering strength within a frequency range of 6–24 kHz was conducted using omnidirectional sources and omnidirectional receiving hydrophones. In this experiment, with interference from scattering off the sea surface being avoided and the far-field condition being satisfied, we obtained acoustic bottom backscattering strength values ranging from −31 to −17 dB within a grazing angle range of 18°–80°. In the effective grazing angle range, the acoustic scattering strength generally increases with the increase in the grazing angle, but the variation trends were different in different frequency bands, which reflects different scattering mechanisms. The frequency dependence of the acoustic backscattering strength is characterized by a segmented correlation. In the frequency band of 6–11 kHz, the scattering strength is positively correlated with the frequency, and the average slope of the linear correlation is about 0.83 ...