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.

Overthrust imaging with tomo‐datuming: A case study

Geophysics ◽  
1998 ◽  
Vol 63 (1) ◽  
pp. 25-38 ◽  
Author(s):  
Xianhuai Zhu ◽  
Burke G. Angstman ◽  
David P. Sixta
Keyword(s):  
Velocity Model ◽  
Surface Velocity ◽  
Time Shift ◽  
Lateral Velocity ◽  
Prestack Depth Migration ◽  
Near Surface ◽  
Depth Migration ◽  
Static Corrections ◽  
Velocity Variations ◽  
Kirchhoff Method

Through the use of iterative turning‐ray tomography followed by wave‐equation datuming (or tomo‐datuming) and prestack depth migration, we generate accurate prestack images of seismic data in overthrust areas containing both highly variable near‐surface velocities and rough topography. In tomo‐datuming, we downward continue shot records from the topography to a horizontal datum using velocities estimated from tomography. Turning‐ray tomography often provides a more accurate near‐surface velocity model than that from refraction statics. The main advantage of tomo‐datuming over tomo‐statics (tomography plus static corrections) or refraction statics is that instead of applying a vertical time‐shift to the data, tomo‐datuming propagates the recorded wavefield to the new datum. We find that tomo‐datuming better reconstructs diffractions and reflections, subsequently providing better images after migration. In the datuming process, we use a recursive finite‐difference (FD) scheme to extrapolate wavefield without applying the imaging condition, such that lateral velocity variations can be handled properly and approximations in traveltime calculations associated with the raypath distortions near the surface for migration are avoided. We follow the downward continuation step with a conventional Kirchhoff prestack depth migration. This results in better images than those migrated from the topography using the conventional Kirchhoff method with traveltime calculation in the complicated near surface. Since FD datuming is only applied to the shallow part of the section, its cost is much less than the whole volume FD migration. This is attractive because (1) prestack depth migration usually is used iteratively to build a velocity model, so both efficiency and accuracy are important factors to be considered; and (2) tomo‐datuming can improve the signal‐to‐noise (S/N) ratio of prestack gathers, leading to more accurate migration velocity analysis and better images after depth migration. Case studies with synthetic and field data examples show that tomo‐datuming is especially helpful when strong lateral velocity variations are present below the topography.

Seismic imaging and velocity analysis for an Alberta Foothills seismic survey

Geophysics ◽  
2001 ◽  
Vol 66 (3) ◽  
pp. 721-732 ◽  
Author(s):  
Lanlan Yan ◽  
Larry R. Lines
Keyword(s):  
Seismic Imaging ◽  
Migration Velocity ◽  
Surface Velocity ◽  
Seismic Survey ◽  
Velocity Analysis ◽  
Prestack Depth Migration ◽  
Near Surface ◽  
Depth Migration ◽  
Migration Velocity Analysis ◽  
Imaging Results

Seismic imaging of complex structures from the western Canadian Foothills can be achieved by applying the closely coupled processes of velocity analysis and depth migration. For the purposes of defining these structures in the Shaw Basing area of western Alberta, we performed a series of tests on both synthetic and real data to find optimum imaging procedures for handling large topographic relief, near‐surface velocity variations, and the complex structural geology of steeply dipping formations. To better understand the seismic processing problems, we constructed a typical foothills geological model that included thrust faults and duplex structures, computed the model responses, and then compared the performance of different migration algorithms, including the explicit finite difference (f-x) and Kirchhoff integral methods. When the correct velocity was used in the migration tests, the f-x method was the most effective in migration from topography. In cases where the velocity model was not assumed known, we determined a macrovelocity model by performing migration/velocity analysis by using smiles and frowns in common image gathers and by using depth‐focusing analysis. In applying depth imaging to the seismic survey from the Shaw Basing area, we found that imaging problems were caused partly by near‐surface velocity problems, which were not anticipated in the modeling study. Several comparisons of different migration approaches for these data indicated that prestack depth migration from topography provided the best imaging results when near‐surface velocity information was incorporated. Through iterative and interpretive migration/velocity analysis, we built a macrovelocity model for the final prestack depth migration.

High‐resolution seismic traveltime tomography incorporating static corrections applied to a till‐covered bedrock environment

Geophysics ◽  
2004 ◽  
Vol 69 (4) ◽  
pp. 1082-1090 ◽  
Author(s):  
Björn Bergman ◽  
Ari Tryggvason ◽  
Christopher Juhlin
Keyword(s):  
High Resolution ◽  
Velocity Model ◽  
Surface Velocity ◽  
Data Set ◽  
Near Surface ◽  
Seismic Processing ◽  
Simultaneous Inversion ◽  
Reflection Seismic ◽  
Static Corrections ◽  
Velocity Variations

A major obstacle in tomographic inversion is near‐surface velocity variations. Such shallow velocity variations need to be known and correctly accounted for to obtain images of deeper structures with high resolution and quality. Bedrock cover in many areas consists of unconsolidated sediments and glacial till. To handle the problems associated with this cover, we present a tomographic method that solves for the 3D velocity structure and receiver static corrections simultaneously. We test the method on first‐arrival picks from deep seismic reflection data acquired in the mid‐ late to 1980s in the Siljan Ring area, central Sweden. To use this data set successfully, one needs to handle a number of problems, including time‐varying, near‐surface velocities from data recorded in winter and summer, several sources and receivers within each inversion cell, varying thickness of the cover layer in each inversion cell, and complex 3D geology. Simultaneous inversion for static corrections and velocity produces a much better image than standard tomography without statics. The velocity model from the simultaneous inversion is superior to the velocity model produced using refraction statics obtained from standard reflection seismic processing prior to inversion. Best results using the simultaneous inversion are obtained when the initial top velocity layer is set to the near‐surface bedrock velocity rather than the velocity of the cover. The resulting static calculations may, in the future, be compared to refraction static corrections in standard reflection seismic processing. The preferred final model shows a good correlation with the mapped geology and the airborne magneticmap.

Near Surface Velocity Model of Dukhan Field from Multi-Physics Survey to Enhance PSDM Seismic Imaging

2015 ◽  
Author(s):  
K. Setiyono ◽  
S. Gallo ◽  
C. Boulange ◽  
F. Bruere ◽  
F. Moreau ◽  
...  
Keyword(s):  
Seismic Imaging ◽  
Velocity Model ◽  
Surface Velocity ◽  
Near Surface

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.

Recent applications of turning-ray tomography

Geophysics ◽  
2008 ◽  
Vol 73 (5) ◽  
pp. VE243-VE254 ◽  
Author(s):  
Xianhuai Zhu ◽  
Paul Valasek ◽  
Baishali Roy ◽  
Simon Shaw ◽  
Jack Howell ◽  
...  
Keyword(s):  
Reservoir Characterization ◽  
Velocity Model ◽  
Surface Velocity ◽  
Seismic Survey ◽  
Structural Imaging ◽  
Prestack Depth Migration ◽  
Near Surface ◽  
Depth Migration ◽  
Time Migration ◽  
Prestack Time Migration

Recent applications of 2D and 3D turning-ray tomography show that near-surface velocities are important for structural imaging and reservoir characterization. For structural imaging, we used turning-ray tomography to estimate the near-surface velocities for static corrections followed by prestack time migration and the near-surface velocities for prestack depth migration. Two-dimensional acoustic finite-difference modeling illustrates that wave-equation prestack depth migration is very sensitive to the near-surface velocities. Field data demonstrate that turning-ray tomography followed by prestack time migration helps to produce superior images in complex geologic settings. When the near-surface velocity model is integrated into a background velocity model for prestack depth migration, we find that wave propagation is very sensitive to the velocities immediately below the topography. For shallow-reservoir characterization, we developed and applied azimuthal turning-ray tomography to investigate observed apparent azimuthal-traveltime variations, using a wide-azimuth land seismic survey from a heavy-oil field at Surmont, Canada. We found that the apparent azimuthal velocity variations are not necessarily related to azimuthal anisotropy, or horizontal transverse isotropy (HTI), induced by the stress field or fractures. Near-surface heterogeneity and the acquisition footprint also could result in apparent azimuthal variations.

Seismic imaging beyond depth migration

Geophysics ◽  
2001 ◽  
Vol 66 (6) ◽  
pp. 1895-1912 ◽  
Author(s):  
A. J. Berkhout ◽  
D. J. Verschuur
Keyword(s):  
Seismic Imaging ◽  
Time Lapse ◽  
Velocity Model ◽  
Surface Layers ◽  
Near Surface ◽  
Depth Migration ◽  
New Type ◽  
Complex Propagation ◽  
The Common ◽  
Focus Point

If seismic imaging is formulated in terms of two focusing steps—focusing in emission and focusing in detection (or vice versa)—the output of the first focusing step yields a new type of seismic gather, the common‐focus‐point (CFP) gather, which is available for data analysis and information extraction. One important consequence of this novel option is that the involved focusing operators can be updated without updating the underlying velocity model. Introducing the concept of “dynamic focusing,” it is proposed to verify the validity of focusing operators by comparing the “gather of focus‐point responses” with the “gather of focusing operators.” Compared with velocity‐driven time and depth migration, operator‐driven CFP migration can be considered as the most general approach to seismic imaging: it does not require a velocity model, and it automatically takes into account unknown complex propagation effects such as conversion, anisotropy, and dispersion. In addition, in CFP migration, the second focusing step can be extended to produce both angle‐averaged reflection information and angle‐dependent reflection information. The CFP approach to seismic migration allows new solutions in the situation of complex near‐surface layers, subsalt targets, multicomponent processing, and time lapse analysis.

Computing near-surface velocity models for S-wave static corrections using raypath interferometry

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. U23-U34
Author(s):  
Raul Cova ◽  
David Henley ◽  
Kristopher A. Innanen
Keyword(s):  
Wave Velocity ◽  
Velocity Model ◽  
P Wave ◽  
Surface Velocity ◽  
S Wave ◽  
Converted Wave ◽  
Near Surface ◽  
Velocity Models ◽  
Consistent Solution ◽  
Static Corrections

A near-surface velocity model is one of the typical products generated when computing static corrections, particularly in the processing of PP data. Critically refracted waves are the input usually needed for this process. In addition, for the converted PS mode, S-wave near-surface corrections must be applied at the receiver locations. In this case, however, critically refracted S-waves are difficult to identify when using P-wave energy sources. We use the [Formula: see text]-[Formula: see text] representation of the converted-wave data to capture the intercept-time differences between receiver locations. These [Formula: see text]-differences are then used in the inversion of a near-surface S-wave velocity model. Our processing workflow provides not only a set of raypath-dependent S-wave static corrections, but also a velocity model that is based on those corrections. Our computed near-surface S-wave velocity model can be used for building migration velocity models or to initialize elastic full-waveform inversions. Our tests on synthetic and field data provided superior results to those obtained by using a surface-consistent solution.

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