Traditional viscoacoustic migration methods effectively compensate for amplitude loss and phase distortion caused by viscous attenuation. However, these methods predominantly focus on achieving accurate structural imaging. Preserving relative-amplitude information in migrated images is crucial for accurately restoring medium properties while imaging geometric structures under viscous attenuation conditions. In this paper, we present an efficient and stable method for viscoacoustic true-amplitude Gaussian beam migration in the common-offset domain, specifically designed to tackle this challenge. Our approach utilizes the multiparameter viscoacoustic Born scattering mechanism to recover the velocity and quality factorQ. The incorporation ofQinto the migration process is achieved by definingQ-related complex-valued traveltime to compensate for attenuation effects. We illustrate the forward single scattering integral for the central beam component of the viscoacoustic common-offset scattered pressure wavefield, using attenuation-compensated Gaussian-beam expansions of the viscoacoustic Green’s function. This description, along with the estimation of the kernel of the single-scattering Hessian operator, enables us to develop a viscoacoustic Gaussian-beam pseudoinverse migration operator for common-offset data. This operator includes a Beylkin determinant and an invertible normal matrix associated with a causality term. Employing this derived pseudoinverse operator enhances subsurface structure imaging accuracy and preserves amplitude response information of material parameters throughout the viscoacoustic migration process. Numerical experiments and field data tests demonstrate that, with the proposed attenuation compensation method, it is possible to align the estimated parameters with their true values, yielding more accurate imaging and parameter estimations in viscoacoustic media compared to the traditional acoustic approach without attenuation compensation.

Full-waveform inversion (FWI) is increasingly used in land seismic exploration to achieve high-resolution near-surface models. In complex near-surface environments, however, FWI is challenged by noisy data and inaccurate initial models, raising the need for an effective regularization strategy to mitigate the inherent ill-posedness of FWI. Incorporating geological information, such as structural dips, into the regularization operator, has proven effective in stabilizing FWI and promoting geologically meaningful results. Obtaining clear seismic images that provide structural insights is, nonetheless often hindered in complex near-surface surveys due to noisy reflection data and gradient weathering velocity. Structural regularization treats imaged reflectors as velocity contours and penalizes velocity variations along the dips. We propose a novel approach involving deformable-layer tomography (DLT) to directly invert for velocity contour distributions. DLT is well suited for near-surface applications as it accommodates both gradient velocity variations and abrupt velocity contrasts. In order to avoid erroneous structural regularization, we evaluate the accuracy of the DLT-estimated dips and assign weights accordingly. The weighted dip field is used to construct directional total variation (TV) in regularizing FWI, using the edge-preserving smoothing of TV regularization as well as the dip constraint. Using a realistic near-surface model, we demonstrate that FWI with the DLT-guided directional TV regularization outperforms conventional TV regularization. Our findings underscore the advantages of incorporating geologic structural constraint into FWI under complex near-surface conditions, highlighting the improved fidelity and resolution in near-surface velocity model building.

In complex near-surface geologic settings, first-arrival traveltime tomography suffers from strong data noise and uneven raypath coverage. To reduce the inversion nonuniqueness, model smoothing is necessary but often without incorporating structural constraints based on seismic images. The reasons include a lack of shallow reflections, strong noise, and gradient velocity field with strong lateral variation. We propose to estimate the near-surface structural trend from the velocity solution of deformable-layer tomography (DLT), that inverts for velocity contours directly. Then the structural dips derived from the DLT solution are taken as the structural regularization in the subsequent traveltime tomographic inversion. Tests for the 2011 Symposium on the Application of Geophysics to Engineering and Environmental Problems (SAGEEP) workshop model illustrate that this DLT-guided structural regularization steers the tomographic inversion toward more accurate near-surface models. The application of the DLT-guided structural regularization to field data reveals the near-surface geology of a beach area in Qingdao, China. The DLT solution could complement seismic images or other structural information in regularizing tomographic inversion.

Seismic migrations are generally formulated as the adjoint operators of linear forward modeling and often lead to images with degraded resolution, unbalanced illumination, and migration artifacts, especially in surveys with geologic complexity and irregular acquisition geometry. Least-squares migration (LSM) is able to mitigate these problems and produce better resolved images that are suitable for subsequent AVO/AVA inversion. However, no matter what domain LSM is implemented in, the computational cost is still several times or even one order of magnitude more than that of the traditional migration. In this article, we present an efficient image-domain least-square Kirchhoff depth migration (LSKDM), in which the Hessian matrix is approximated by a grid of point-spread-functions (PSFs). Traditional PSF computing algorithm requires a nonnegligible cost caused by a successive operation of modeling and migration and has to satisfy a sampling restriction to avoid interference between nearby PSFs. We present in this article that, by using the ray-based Green’s functions and the linear traveltime approximation, the PSFs can be constructed explicitly at a significantly reduced computational cost and are able to adapt flexible spatial sampling that is fine enough to detect small-scale illumination variation. With the constructed PSFs, we formulate an image-domain LSKDM to iteratively solve for the optimal reflectivities. Numerical tests on synthetic and field data examples demonstrate that the proposed LSKDM is highly efficient and is capable of producing images with enhanced spatial resolution and amplitude fidelity when compared with the Kirchhoff depth migration (KDM) image.

Conventional vertical seismic profiling (VSP) wavefield separation method (CSM) focuses on the wavefield separation result, not the residual. Usually, it cannot obtain desirable high-precision results. Iterative zero-offset VSP (ZVSP). However, IZSM only can be used for ZVSP data, which limits its application. The scalar wavefield separation algorithm used in IZSM is based on the SVD filtering, which limits its precision. The objective function threshold of IZSM is varied with the input ZVSP data, which limits its result precision and efficiency. To improve the wavefield separation precision and efficiency, we propose a high-precision iterative VSP wavefield separation method (HISM). HISM is suitable for both ZVSP and offset VSP (OVSP) data, and also applicable for any possible scalar wavefield separation algorithm The objective function threshold of HISM can be a fixed number. Therefore, HISM can obtain high precision and efficiency results. Actual ZVSP and OVSP data application demonstrates the performance of HISM.

High-speed train (HST) generates strong and repeatable vibrations that could be used for subsurface imaging and monitoring. Compared with other ambient noise, HST vibrations are generated by a moving source and have striking characteristics as a deterministic source. However, little attention has been paid to the effects of the characteristics of HST sources on the seismic wave retrieval using seismic interferometry. The aim of this study is to investigate what types of seismic waves are retrievable by applying seismic interferometry to HST-induced vibrations. By analyzing the cross correlation of the HST-induced vibrations between two receivers, we find that cross terms are introduced during the cross correlation. These cross terms are nonnegligible for reflection-wave retrieval but can be negligible for the retrieval of direct waves, scattered waves, and refraction waves. This finding has been validated by field data tests. We further demonstrate that the retrieved surface waves can be used to estimate near-surface velocities and that the retrieved scattered surface waves can be used to locate near-surface heterogeneous bodies.

A new Gaussian beam (GB) Born modeling method is presented in this letter to simulate the wavefields of single scattering events in visco-acoustic media. This approach allows the accurate computation of synthetic seismograms or waveforms for the visco-acoustic media. Our method relies on the GB summation method, in which the attenuation effects are taken into account by incorporating a frequency-dependent dissipation function into beam calculation. The key to efficiency is that the Born modeling kernel is evaluated in the time domain based on the filter-bank technique. The proposed method is tested with both 2-D and 3-D numerical examples and the results demonstrate its capability to simulate wavefields in complex structures, as well as its marked advantage in efficiency over finite-difference wave equation modeling.