Refined field static corrections in near‐surface reflection profiling across rugged terrain

1995 ◽  
Vol 14 (4) ◽  
pp. 259-262 ◽  
Author(s):  
Walter Frei
Keyword(s):  
Near Surface ◽  
Surface Reflection ◽  
Rugged Terrain ◽  
Static Corrections ◽  
Field Static

Pitfalls in processing near-surface reflection-seismic data: Beware of static corrections and migration

2015 ◽  
Vol 34 (11) ◽  
pp. 1382-1385 ◽  
Author(s):  
W. Frei ◽  
R. Bauer ◽  
Ph. Corboz ◽  
D. Martin
Keyword(s):  
Seismic Data ◽  
Near Surface ◽  
Surface Reflection ◽  
Reflection Seismic ◽  
Static Corrections ◽  
And Migration

Simultaneous estimation of residual static and crossdip corrections

Geophysics ◽  
1979 ◽  
Vol 44 (7) ◽  
pp. 1175-1192 ◽  
Author(s):  
Kenneth L. Larner ◽  
Bruce R. Gibson ◽  
Ron Chambers ◽  
Ralph A. Wiggins
Keyword(s):  
Three Dimensional ◽  
Synthetic Data ◽  
Simultaneous Estimation ◽  
Broad Line ◽  
Near Surface ◽  
Seismic Surveys ◽  
Surface Reflection ◽  
Static Corrections ◽  
Solution Parameters

Seismic surveys on land are frequently conducted along nonlinear survey lines. Familiar examples include crooked lines controlled by existing road networks or by surface typography, lines that are otherwise linear but along which shotpoints occasionally must be offset laterally, and intentionally designed three‐dimensional (3-D) or broad‐line surveys. Departures from linear profiles introduce an element of complexity—crossdip—into the problem of estimating residual near‐surface reflection static time corrections (statics). Crossdip is the component of dip normal to the local profile direction. We have incorporated the effect of crossdip into the system of simultaneous equations that model residual static anomalies. The observed traveltimes of all reflections selected for analysis are represented as linear combinations of source and receiver static anomalies, structural shapes, residual normal moveouts, and crossdip terms. The static time components are taken to be surface‐consistent and independent of reflecting horizon, whereas the other solution parameters are subsurface‐consistent and pertain to specific horizons. Unfortunately, the inclusion of crossdip in the equations increases the degree of nonuniqueness of residual statics solutions. Its inclusion, however, is a necessity wherever horizons having differing crossdips are analyzed simultaneously. Such simultaneous analysis often is the best means for upgrading the reliability of the crosscorrelation estimates (i.e., the traveltime observations) upon which all statics are based. Synthetic‐data examples demonstrate the degree to which crossdip estimates and statics estimates can be separated from one another. Although estimates of crossdips are a useful by‐product, the accuracy of the static corrections is considered of prime importance. When critical crossdip terms are ignored in a statics solution, the quality of the common‐depthpoint (CDP) stacks suffer, as shown in comparison processings of field sections. Moreover, crossdip estimates from 3-D or broad‐line surveys are questionable if crossdip and static corrections are not considered in a unified solution.

A NEW DATA‐PROCESSING TECHNIQUE FOR THE ELIMINATION OF GHOST ARRIVALS ON REFLECTION SEISMOGRAMS

Geophysics ◽  
1964 ◽  
Vol 29 (5) ◽  
pp. 783-805 ◽  
Author(s):  
William A. Schneider ◽  
Kenneth L. Larner ◽  
J. P. Burg ◽  
Milo M. Backus
Keyword(s):  
Data Processing ◽  
Filter Design ◽  
Random Noise ◽  
Wide Band ◽  
Processing Technique ◽  
Linear Filter ◽  
Least Mean Square ◽  
Near Surface ◽  
Surface Reflection ◽  
Data Processing Technique

A new data‐processing technique is presented for the separation of initially up‐traveling (ghost) energy from initially down‐traveling (primary) energy on reflection seismograms. The method combines records from two or more shot depths after prefiltering each record with a different filter. The filters are designed on a least‐mean‐square‐error criterion to extract primary reflections in the presence of ghost reflections and random noise. Filter design is dependent only on the difference in uphole time between shots, and is independent of the details of near‐surface layering. The method achieves wide‐band separation of primary and ghost energy, which results in 10–15 db greater attenuation of ghost reflections than can be achieved with conventional two‐ or three‐shot stacking (no prefiltering) for ghost elimination. The technique is illustrated in terms of both synthetic and field examples. The deghosted field data are used to study the near‐surface reflection response by computing the optimum linear filter to transform the deghosted trace back into the original ghosted trace. The impulse response of this filter embodies the effects of the near‐surface on the reflection seismogram, i.e. the cause of the ghosting. Analysis of these filters reveals that the ghosting mechanism in the field test area consists of both a surface‐ and base‐of‐weathering layer reflector.

Estimation of Near-Surface Velocity for 3-D Complicated Topography and Seismic Tomographic Static Corrections

2001 ◽  
Vol 44 (2) ◽  
pp. 268-274 ◽  
Author(s):  
Yi-Ke LIU ◽  
Xu CHANG ◽  
Hui WANG ◽  
Fu-Zhong LI
Keyword(s):  
Surface Velocity ◽  
Near Surface ◽  
Static Corrections

scholarly journals Muting the noise cone in near‐surface reflection data: An example from southeastern Kansas

Geophysics ◽  
1998 ◽  
Vol 63 (4) ◽  
pp. 1332-1338 ◽  
Author(s):  
Gregory S. Baker ◽  
Don W. Steeples ◽  
Matt Drake
Keyword(s):  
Data Processing ◽  
Seismic Data ◽  
Hydrocarbon Exploration ◽  
Seismic Reflection Profile ◽  
Seismic Data Processing ◽  
Near Surface ◽  
Surface Reflection ◽  
Reflection Data ◽  
Data Volume ◽  
Total Data

A 300-m near‐surface seismic reflection profile was collected in southeastern Kansas to locate a fault(s) associated with a recognized stratigraphic offset on either side of a region of unexposed bedrock. A substantial increase in the S/N ratio of the final stacked section was achieved by muting all data arriving in time after the airwave. Methods of applying traditional seismic data processing techniques to near‐surface data (200 ms of data or less) often differ notably from hydrocarbon exploration‐scale processing (3–4 s of data or more). The example of noise cone muting used is contrary to normal exploration‐scale seismic data processing philosophy, which is to include all data containing signal. The noise cone mute applied to the data removed more than one‐third of the total data volume, some of which contains signal. In this case, however, the severe muting resulted in a higher S/N ratio in the final stacked section, even though some signal could be identified within the muted data. This example supports the suggestion that nontraditional techniques sometimes need to be considered when processing near‐surface seismic data.

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.

3‐D tomographic static correction

Geophysics ◽  
2002 ◽  
Vol 67 (4) ◽  
pp. 1275-1285 ◽  
Author(s):  
Xu Chang ◽  
Yike Liu ◽  
Hui Wang ◽  
Fuzhong Li ◽  
Jing Chen
Keyword(s):  
Computation Time ◽  
Matrix Decomposition ◽  
Velocity Model ◽  
Seismic Survey ◽  
Surface Model ◽  
Low Velocity ◽  
Near Surface ◽  
Model Inversion ◽  
Static Corrections ◽  
Refracted Waves

A 3‐D tomographic inversion approach based on a surface‐consistent model for static corrections is presented in this paper. Direct, reflected, and refracted waves are used simultaneously to update the near‐surface model. We analyze the characteristics of the first‐break traveltime in complicated low‐velocity layers. To improve the accuracy for the velocity model, the various first‐break times from direct, reflected, and refracted waves are considered for model inversion. A fractal algorithm which overcomes the error caused by wavelet shape differences is applied to pick first breaks. It also overcomes the leg jump of refractions. The method can pick a large number of first breaks automatically. The raypaths and traveltimes are calculated with a 3‐D ray tracer that does not increase computation time for complicated geological models. Our method can determine the raypath associated with minimum traveltimes regardless of wave mode (direct, refracted, or reflected). We use a least‐squares approach in conjunction with a matrix decomposition to reconstruct a 3‐D velocity model from the actual first‐break times obtained from 3‐D data. Finally, long‐ and short‐wavelength static corrections are calculated concurrently, based on the reconstructed velocity profile. The method can be applied to wide‐line profiles, crooked lines, and 2‐D and 3‐D seismic survey geometries. The results applied to a real 3‐D data example indicate that the 3‐D tomographic static corrections are effective for field data.

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