Near surface velocity estimation using the flatness of angle gathers without horizon

2020 ◽  
Author(s):  
Kwangjin Yoon ◽  
Yi Luo
Keyword(s):  
Velocity Estimation ◽  
Surface Velocity ◽  
Near Surface

Surface-Wave Simulation for the Continuously Moving Seismic Sources

2021 ◽  
Author(s):  
Yuefeng Yan ◽  
Chengyu Sun ◽  
Tengfei Lin ◽  
Jiao Wang ◽  
Jidong Yang ◽  
...  
Keyword(s):  
Rayleigh Waves ◽  
Frequency Dispersion ◽  
Dispersion Curves ◽  
Velocity Estimation ◽  
Surface Velocity ◽  
Seismic Sources ◽  
Near Surface ◽  
Moving Source ◽  
Source Data ◽  
Doppler Effects

Abstract In exploration and earthquake seismology, most sources used in subsurface structure imaging and rock property estimation are fixed in certain positions. Continuously moving seismic sources, such as vehicles and the metro, are one kind of important passive sources in ambient noise research. Commonly, seismic data acquisition and processing for moving sources are based on the assumption of simple point passive sources, and the dispersion curve inversion is applied to constrain near-surface velocity. This workflow neglects the Doppler effects. Considering the continuously moving properties of the sources, we first derive the analytical solution for the Rayleigh waves excited by heavy vehicles and then analyze their Doppler effects and dispersion curves. We observe that the moving source data have the Doppler effect when compared with the changes in the frequency of the source intensity, but this effect does not affect the frequency dispersion of Rayleigh waves. The dispersion curves computed for moving source records are consistent with the analytical dispersion solutions, which provide a theoretical foundation for velocity estimation using moving source data.

Novel strategies for complex foothills seismic imaging — Part 1: Mega-near-surface velocity estimation

2020 ◽  
Vol 8 (3) ◽  
pp. T651-T665
Author(s):  
Yalin Li ◽  
Xianhuai Zhu ◽  
Gengxin Peng ◽  
Liansheng Liu ◽  
Wensheng Duan
Keyword(s):  
Seismic Imaging ◽  
Velocity Model ◽  
Velocity Estimation ◽  
Innovative Approach ◽  
Surface Velocity ◽  
Near Surface ◽  
Depth Migration ◽  
Static Corrections ◽  
Over Time

Seismic imaging in foothills areas is challenging because of the complexity of the near-surface and subsurface structures. Single seismic surveys often are not adequate in a foothill-exploration area, and multiple phases with different acquisition designs within the same block are required over time to get desired sampling in space and azimuths for optimizing noise attenuation, velocity estimation, and migration. This is partly because of economic concerns, and it is partly because technology is progressing over time, creating the need for unified criteria in processing workflows and parameters at different blocks in a study area. Each block is defined as a function of not only location but also the acquisition and processing phase. An innovative idea for complex foothills seismic imaging is presented to solve a matrix of blocks and tasks. For each task, such as near-surface velocity estimation and static corrections, signal processing, prestack time migration, velocity-model building, and prestack depth migration, one or two best service companies are selected to work on all blocks. We have implemented streamlined processing efficiently so that Task-1 to Task-n progressed with good coordination. Application of this innovative approach to a mega-project containing 16 3D surveys covering more than [Formula: see text] in the Kelasu foothills, northwestern China, has demonstrated that this innovative approach is a current best practice in complex foothills imaging. To date, this is the largest foothills imaging project in the world. The case study in Kelasu successfully has delivered near-surface velocity models using first arrivals picked up to 3500 m offset for static corrections and 9000 m offset for prestack depth migration from topography. Most importantly, the present megaproject is a merge of several 3D surveys, with the merge performed in a coordinated, systematic fashion in contrast to most land megaprojects. The benefits of this approach and the strategies used in processing data from the various subsurveys are significant. The main achievement from the case study is that the depth images, after the application of the near-surface velocity model estimated from the megasurveys, are more continuous and geologically plausible, leading to more accurate seismic interpretation.

Near-surface velocity estimation using source-domain full traveltime inversion and early arrival waveform inversion

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. R335-R344 ◽  
Author(s):  
Lu Liu ◽  
Yan Wu ◽  
Bowen Guo ◽  
Song Han ◽  
Yi Luo
Keyword(s):  
Plane Wave ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Velocity Estimation ◽  
Surface Velocity ◽  
Accurate Estimation ◽  
Near Surface ◽  
Traveltime Inversion ◽  
Source Domain ◽  
Early Arrival

Accurate estimation of near-surface velocity is a key step for imaging deeper targets. We have developed a new workflow to invert complex early arrivals in land seismic data for near-surface velocities. This workflow is composed of two methods: source-domain full traveltime inversion (FTI) and early arrival waveform inversion (EWI). Source-domain FTI automatically generates the background velocity that kinematically matches the reconstructed plane-wave sources from early arrivals with true plane-wave sources. This method does not require picking first arrivals for inversion, which is one of the most challenging and labor-intensive steps in ray-based first-arrival traveltime tomography, especially when the subsurface medium contains low-velocity zones that cause shingled multivalue arrivals. Moreover, unlike the conventional Born-based method, source-domain FTI can determine if the initial velocity is slower or faster than the true one according to the gradient sign. In addition, the computational cost is reduced considerably by using the one-way wave equation to extrapolate the plane-wave Green’s function. The source-domain FTI tomogram is then used as the starting model for EWI to obtain the short-wavelength component associated with the velocity model. We tested the workflow on two synthetic and one onshore filed data sets. The results demonstrate that source-domain FTI generates reasonable background velocities for EWI even though the first arrivals are shingled, and that this workflow can produce a high-resolution near-surface velocity model.

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