ESTIMATION AND CORRECTION OF NEAR‐SURFACE TIME ANOMALIES

Geophysics ◽  
1974 ◽  
Vol 39 (4) ◽  
pp. 441-463 ◽  
Author(s):  
M. Turhan Taner ◽  
F. Koehler ◽  
K. A. Alhilali
Keyword(s):  
Real Data ◽  
Least Square ◽  
Seismic Reflection Data ◽  
Near Surface ◽  
Reflection Data ◽  
Common Depth Point ◽  
Surface Time ◽  
Before And After ◽  
Nmo Correction ◽  
Static Corrections

The problem of computing static corrections for CDP seismic reflection data is discussed. A new approach is presented and it is related to various existing approaches. The approach consists of using crosscorrelation computations to find time shifts which appear to align the traces of each common‐depth‐point. These shifts are expressed in terms of surface corrections, one for each source and receiver position; a residual NMO correction for each common‐depth‐point; and a fixed correction for each common‐depth‐point. These simultaneous equations form an overdetermined set which can be solved for the unknown static and NMO corrections. The least‐square‐error solution to these equations has an important indeterminancy which is discussed. Methods for its resolution are proposed. Application of the technique to real data is illustrated by several examples. Validity of the corrections is demonstrated by velocity analyses before and after correction of the traces.

Tomographic determination of velocity and depth in laterally varying media

Geophysics ◽  
1985 ◽  
Vol 50 (6) ◽  
pp. 903-923 ◽  
Author(s):  
T. N. Bishop ◽  
K. P. Bube ◽  
R. T. Cutler ◽  
R. T. Langan ◽  
P. L. Love ◽  
...  
Keyword(s):  
Seismic Reflection ◽  
Seismic Velocity ◽  
Real Data ◽  
Seismic Reflection Data ◽  
Near Surface ◽  
Reflection Data ◽  
Tomographic Method ◽  
Recorded Data ◽  
The Difference

Estimation of reflector depth and seismic velocity from seismic reflection data can be formulated as a general inverse problem. The method used to solve this problem is similar to tomographic techniques in medical diagnosis and we refer to it as seismic reflection tomography. Seismic tomography is formulated as an iterative Gauss‐Newton algorithm that produces a velocity‐depth model which minimizes the difference between traveltimes generated by tracing rays through the model and traveltimes measured from the data. The input to the process consists of traveltimes measured from selected events on unstacked seismic data and a first‐guess velocity‐depth model. Usually this first‐guess model has velocities which are laterally constant and is usually based on nearby well information and/or an analysis of the stacked section. The final model generated by the tomographic method yields traveltimes from ray tracing which differ from the measured values in recorded data by approximately 5 ms root‐mean‐square. The indeterminancy of the inversion and the associated nonuniqueness of the output model are both analyzed theoretically and tested numerically. It is found that certain aspects of the velocity field are poorly determined or undetermined. This technique is applied to an example using real data where the presence of permafrost causes a near‐surface lateral change in velocity. The permafrost is successfully imaged in the model output from tomography. In addition, depth estimates at the intersection of two lines differ by a significantly smaller amount than the corresponding estimates derived from conventional processing.

Traveltime tomographic inversion with simultaneous static corrections — Well worth the effort

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. WCB25-WCB33 ◽  
Author(s):  
Ari Tryggvason ◽  
Cedric Schmelzbach ◽  
Christopher Juhlin
Keyword(s):  
Seismic Reflection ◽  
Real Data ◽  
Seismic Velocities ◽  
Low Velocity ◽  
Data Set ◽  
Detailed Model ◽  
Seismic Reflection Data ◽  
Near Surface ◽  
First Arrival ◽  
Static Corrections

We have developed a first-arrival traveltime inversion scheme that jointly solves for seismic velocities and source and receiver static-time terms. The static-time terms are included to compensate for varying time delays introduced by the near-surface low-velocity layer that is too thin to be resolved by tomography. Results on a real data set consisting of picked first-arrival times from a seismic-reflection 2D/3D experiment in a crystalline environment show that the tomography static-time terms are very similar in values and distribution to refraction-static corrections computed using standard refraction-statics software. When applied to 3D seismic-reflection data, tomography static-time terms produce similar or more coherent seismic-reflection images compared to the images using corrections from standard refraction-static software. Furthermore, the method provides a much more detailed model of the near-surface bedrock velocity than standard software when the static-time terms are included in the inversion. Low-velocity zones in this model correlate with other geologic and geophysical data, suggesting that our method results in a reliable model. In addition to generally being required in seismic-reflection imaging, static corrections are also necessary in traveltime tomography to obtain high-fidelity velocity images of the subsurface.

An improved method to estimate Q based on the logarithmic spectrum of moving peak points

2019 ◽  
Vol 7 (2) ◽  
pp. T255-T263 ◽  
Author(s):  
Yanli Liu ◽  
Zhenchun Li ◽  
Guoquan Yang ◽  
Qiang Liu
Keyword(s):  
Seismic Waves ◽  
Wave Attenuation ◽  
Real Data ◽  
Peak Frequency ◽  
Seismic Reflection Data ◽  
The Real ◽  
Time Frequency ◽  
Reflection Data ◽  
Text Filtering ◽  
The Impact

The quality factor ([Formula: see text]) is an important parameter for measuring the attenuation of seismic waves. Reliable [Formula: see text] estimation and stable inverse [Formula: see text] filtering are expected to improve the resolution of seismic data and deep-layer energy. Many methods of estimating [Formula: see text] are based on an individual wavelet. However, it is difficult to extract the individual wavelet precisely from seismic reflection data. To avoid this problem, we have developed a method of directly estimating [Formula: see text] from reflection data. The core of the methodology is selecting the peak-frequency points to linear fit their logarithmic spectrum and time-frequency product. Then, we calculated [Formula: see text] according to the relationship between [Formula: see text] and the optimized slope. First, to get the peak frequency points at different times, we use the generalized S transform to produce the 2D high-precision time-frequency spectrum. According to the seismic wave attenuation mechanism, the logarithmic spectrum attenuates linearly with the product of frequency and time. Thus, the second step of the method is transforming a 2D spectrum into 1D by variable substitution. In the process of transformation, we only selected the peak frequency points to participate in the fitting process, which can reduce the impact of the interference on the spectrum. Third, we obtain the optimized slope by least-squares fitting. To demonstrate the reliability of our method, we applied it to a constant [Formula: see text] model and the real data of a work area. For the real data, we calculated the [Formula: see text] curve of the seismic trace near a well and we get the high-resolution section by using stable inverse [Formula: see text] filtering. The model and real data indicate that our method is effective and reliable for estimating the [Formula: see text] value.

Structural interpretation using refraction velocities from marine seismic surveys

Geophysics ◽  
1986 ◽  
Vol 51 (1) ◽  
pp. 12-19 ◽  
Author(s):  
James F. Mitchell ◽  
Richard J. Bolander
Keyword(s):  
Sedimentary Rock ◽  
Seismic Energy ◽  
Seismic Survey ◽  
Subsurface Structure ◽  
Seismic Reflection Data ◽  
Near Surface ◽  
Reflection Data ◽  
Wide Range ◽  
Streamer Length ◽  
Set Up

Subsurface structure can be mapped using refraction information from marine multichannel seismic data. The method uses velocities and thicknesses of shallow sedimentary rock layers computed from refraction first arrivals recorded along the streamer. A two‐step exploration scheme is described which can be set up on a personal computer and used routinely in any office. It is straightforward and requires only a basic understanding of refraction principles. Two case histories from offshore Peru exploration demonstrate the scheme. The basic scheme is: step (1) shallow sedimentary rock velocities are computed and mapped over an area. Step (2) structure is interpreted from the contoured velocity patterns. Structural highs, for instance, exhibit relatively high velocities, “retained” by buried, compacted, sedimentary rocks that are uplifted to the near‐surface. This method requires that subsurface structure be relatively shallow because the refracted waves probe to depths of one hundred to over one thousand meters, depending upon the seismic energy source, streamer length, and the subsurface velocity distribution. With this one requirement met, we used the refraction method over a wide range of sedimentary rock velocities, water depths, and seismic survey types. The method is particularly valuable because it works well in areas with poor seismic reflection data.

STACKING OF REFLECTIONS FROM COMPLEX STRUCTURES

Geophysics ◽  
1974 ◽  
Vol 39 (4) ◽  
pp. 427-440 ◽  
Author(s):  
Max K. Miller
Keyword(s):  
Deep Structure ◽  
Control Model ◽  
Layer Model ◽  
Low Velocity ◽  
Seismic Reflection Data ◽  
Near Surface ◽  
Static Correction ◽  
Reflection Data ◽  
Actual Field ◽  
Interval Velocities

Common‐depth‐point seismic reflection data were generated on a computer using simple ray tracing and analyzed with processing techniques currently used on actual field recordings. Constant velocity layers with curved interfaces were used to simulate complex geologic shapes. Two models were chosen to illustrate problems caused by curved geologic interfaces, i.e., interfaces at depths which vary laterally in a nonlinear fashion and produce large spatial variations in the apparent stacking velocity. A three‐layer model with a deep structure and no weathering was used as a control model. For comparison, a low velocity weathering layer also of variable thickness was inserted near the surface of the control model. The low velocity layer was thicker than the ordinary thin weathering layers where state‐of‐the‐art static correction methods work well. Traveltime, moveout, apparent rms velocities, and interval velocities were calculated for both models. The weathering introduces errors into the rms velocities and traveltimes. A method is described to compensate for these errors. A static correction applied to the traveltimes reduced the fluctuation of apparent rms velocities. Values for the thick weathering layer model were “over corrected” so that synclines (anticlines) replaced false anticlines (synclines) for both near‐surface and deep zones. It is concluded that computer modeling is a useful tool for analyzing specific problems of processing CDP seismic data such as errors in velocity estimates produced by large lateral variations in overburden.

A multioffset, three‐component VSP study in the Sudbury Basin

Geophysics ◽  
1995 ◽  
Vol 60 (2) ◽  
pp. 341-353 ◽  
Author(s):  
Xiao‐Gui Miao ◽  
Wooil M. Moon ◽  
B. Milkereit
Keyword(s):  
Data Processing ◽  
Seismic Reflection ◽  
Velocity Structure ◽  
Least Square ◽  
Seismic Reflection Data ◽  
S Waves ◽  
Velocity Models ◽  
Reflection Data ◽  
Wavefield Separation ◽  
Vsp Data

A multioffset, three‐component vertical seismic profiling (VSP) experiment was carried out in the Sudbury Basin, Ontario, as a part of the LITHOPROBE Sudbury Transect. The main objectives were determination of the shallow velocity structure in the middle of the Sudbury Basin, development of an effective VSP data processing flow, correlation of the VSP survey results with the surface seismic reflection data, and demonstration of the usefulness of the VSP method in a crystalline rock environment. The VSP data processing steps included rotation of the horizontal component data, traveltime inversion for velocity analysis, Radon transform for wavefield separation, and preliminary analysis of shear‐wave data. After wavefield separation, the flattened upgoing wavefields for both P‐waves and S‐waves display consistent reflection events from three depth levels. The VSP-CDP transformed section and corridor stacked section correlate well with the high‐resolution surface reflection data. In addition to obtaining realistic velocity models for both P‐ and S‐waves through least‐square inversion and synthetic seismic modeling for the Chelmsford area, the VSP experiment provided an independent estimation for the reflector dip using three component hodogram analysis, which indicates that the dip of the contact between the Chelmsford and Onwatin formations, at an approximate depth of 380 m in the Chelmsford borehole, is approximately 10.5° southeast. This study demonstrates that multioffset, three‐component VSP experiments can provide important constraints and auxiliary information for shallow crustal seismic studies in crystalline terrain. Thus, the VSP technique bridges the gap between the surface seismic‐reflection technique and well‐log surveys.

Automating the acquisition of 3D near‐surface seismic reflection data

2009 ◽  
Author(s):  
Steven D. Sloan ◽  
Don W. Steeples ◽  
Georgios P. Tsoflias ◽  
Mihan H. McKenna
Keyword(s):  
Seismic Reflection ◽  
Seismic Reflection Data ◽  
Near Surface ◽  
Reflection Data

Another look at NMO stretch

Geophysics ◽  
1992 ◽  
Vol 57 (5) ◽  
pp. 749-751 ◽  
Author(s):  
Arthur E. Barnes
Keyword(s):  
Seismic Reflection ◽  
Qualitative Assessment ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
Amplitude Spectra ◽  
Nmo Correction ◽  
Zero Offset ◽  
Nmo Stretch ◽  
Dominant Frequencies

The normal moveout (NMO) correction is applied to seismic reflection data to transform traces recorded at non‐zero offset into traces that appear to have been recorded at zero offset; this introduces undesirable distortions called NMO stretch (Buchholtz, 1972). NMO stretch must be understood because it lengthens waveforms and thereby reduces resolution. Buchholtz (1972) gives a qualitative assessment of NMO stretch, Dunkin and Levin (1973) derive its effect on the amplitude spectra of narrow waveforms, while Yilmaz (1987, p. 160) considers its effect on dominant frequencies. These works are approximate and do not show how spectral distortions vary through time.

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