Born modelling propagates a wavefield in a “background” velocity model. This wavefield interacts with a provided scattering potential at each time step to produce a source term for a second wavefield.

2023年8月21日 · Least squares reverse time migration (LSRTM) imaging is the one of the most accurate methods for migration imaging at present, and Polak–Ribiere–Polyak conjugate...

Simultaneous-source acquisition technology can obtain better spatial-sampled blended seismic data with significantly faster efficiency in field survey. However, the strong cross-talk noise would be introduced in the final image by directly imaging of blended data. To solve this problem, I propose three direct imaging methods of blended-data.

2025年3月31日 · 最小二乘逆时偏移（LSRTM）相对于常规逆时偏移（RTM）具有分辨率更高、振幅更准确、噪音更少等优势，可以对复杂的地质构造进行有效的成像.这种迭代更新反演成像方法十分依赖目标函数的梯度质量和计算效率.当地质模型中存在强反射界面或者记录中存在折射波时，基于常规互相关成像条件（CCC）的最小二乘逆时偏移梯度会包含很强的低频噪音，从而使反演的收敛速度和成像质量降低.为此，本文在最小二乘逆时偏移的梯度中引进了逆散射成像条件来压 …

Abstract: Least-squares reverse-time migration (LSRTM) is linearized inversion based on the Born approximation, which commonly seeks to high-quality migration result by the least-squares sense.

2023年9月5日 · Least-squares reverse-time migration (LSRTM) solves RTM imaging as a least-squares inversion problem and achieves an imaging result that best matches GPR observation data by implementing an iterative algorithm [19].

Least-squares reverse time migration (LSRTM) is a powerful tool in seeking broadband-wavenumber reflectivity images. It produces better images over reverse-time migration (RTM) at the expense of computational cost. The Hessian effect can be measured in the image domain with the point-spread function (PSF).

2023年6月1日 · Considering the above two problems, this paper derives the least-squares reverse time migration in three-dimensional vertical transversely isotropic media (3D-VTI-LSRTM) and develops a workflow which can realize 3D-LSRTM in VTI media based on this theory. Our workflow uses multi-GPU acceleration and heterogeneous CPU/GPU parallelism.

2025年2月9日 · Extending least-squares reverse time migration (LSRTM) to tilted transverse isotropic (TTI) media (TTI-LSRTM) improves imaging accuracy. However, TTI-LSRTM necessitates multiple migration parameters, including velocity, density, anisotropy parameters, and symmetry axis tilt angle θt of the stratum.

We have developed a method for elastic least-squares reverse time migration (LSRTM) based on a new perturbation imaging condition that yields scalar images of squared P- and S-velocity perturbations. These perturbation images do not suffer from polarity reversals that are common for more conventional elastic imaging methods.