STATISTICALLY OPTIMAL STACKING OF SEISMIC DATA

Geophysics ◽  
1970 ◽  
Vol 35 (3) ◽  
pp. 436-446 ◽  
Author(s):  
John C. Robinson
Keyword(s):  
Seismic Data ◽  
Field Data ◽  
Mean Value ◽  
Seismic Model ◽  
Seismic Record ◽  
Signal To Noise ◽  
Statistical Procedures ◽  
Common Depth Point ◽  
Noise Energy ◽  
Seismic Records

A theory for weighting seismic records in the stacking process has been developed from a statistical seismic model. The model applies to common‐depth‐point seismic records which have been statically and dynamically corrected; the same model applies to an ordinary stacking procedure. The model stipulates for the signal and noise components, respectively, of a seismic record that (1) the signal is coincident with and similarly shaped to the signal on other records, and (2) the noise is statistically independent of that on any other record and of the signal and has zero mean value. In accord with the model, a seismic record is completely described for the purpose of weighting by its signal scale and its signal‐to‐noise energy ratio. Several statistical procedures for evaluating these parameters for seismic field data are presented. The most favorable procedure is demonstrated with both synthetic and field seismic records.

Radon Transform Removes Correlation Noise Produced by Vibroseis

2014 ◽  
Vol 672-674 ◽  
pp. 1964-1967
Author(s):  
Jun Qiu Wang ◽  
Jun Lin ◽  
Xiang Bo Gong
Keyword(s):  
Radon Transform ◽  
Seismic Data ◽  
Cross Correlation ◽  
Random Noise ◽  
Seismic Record ◽  
Electromagnetic Drive ◽  
Seismic Records ◽  
Correlation Noise

Vibroseis obtained the seismic record by cross-correlation detection calculation. compared with dynamite source, cross-correlation detection can suppress random noise, but produce more correlation noise. This paper studies Radon transform to remove correlation noise produced by electromagnetic drive vibroseis and impact rammer. From the results of processing field seismic records, we can see that Radon transform can remove correlation noise by vibroseis, the SNR of vibroseis seismic data is effectively improved.

scholarly journals High-resolution coherency functionals for velocity analysis: An application for subbasalt seismic exploration

Geophysics ◽  
2013 ◽  
Vol 78 (5) ◽  
pp. U53-U63 ◽  
Author(s):  
Andrea Tognarelli ◽  
Eusebio Stucchi ◽  
Alessia Ravasio ◽  
Alfredo Mazzotti
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Field Data ◽  
Signal To Noise Ratio ◽  
Synthetic Seismograms ◽  
Seismic Exploration ◽  
Velocity Analysis ◽  
Signal To Noise ◽  
Geologic Setting ◽  
Analytic Signals

We tested the properties of three different coherency functionals for the velocity analysis of seismic data relative to subbasalt exploration. We evaluated the performance of the standard semblance algorithm and two high-resolution coherency functionals based on the use of analytic signals and of the covariance estimation along hyperbolic traveltime trajectories. Approximate knowledge of the wavelet was exploited to design appropriate filters that matched the primary reflections, thereby further improving the ability of the functionals to highlight the events of interest. The tests were carried out on two synthetic seismograms computed on models reproducing the geologic setting of basaltic intrusions and on common midpoint gathers from a 3D survey. Synthetic and field data had a very low signal-to-noise ratio, strong multiple contamination, and weak primary subbasalt signals. The results revealed that high-resolution coherency functionals were more suitable than semblance algorithms to detect primary signals and to distinguish them from multiples and other interfering events. This early discrimination between primaries and multiples could help to target specific signal enhancement and demultiple operations.

Stacking seismic data using local correlation

Geophysics ◽  
2009 ◽  
Vol 74 (3) ◽  
pp. V43-V48 ◽  
Author(s):  
Guochang Liu ◽  
Sergey Fomel ◽  
Long Jin ◽  
Xiaohong Chen
Keyword(s):  
Seismic Data ◽  
Field Data ◽  
Signal To Noise Ratio ◽  
Random Noise ◽  
Image Point ◽  
Local Correlation ◽  
Seismic Profiles ◽  
Signal To Noise ◽  
Prestack Migration

Stacking plays an important role in improving signal-to-noise ratio and imaging quality of seismic data. However, for low-fold-coverage seismic profiles, the result of conventional stacking is not always satisfactory. To address this problem, we have developed a method of stacking in which we use local correlation as a weight for stacking common-midpoint gathers after NMO processing or common-image-point gathers after prestack migration. Application of the method to synthetic and field data showed that stacking using local correlation can be more effective in suppressing random noise and artifacts than other stacking methods.

Prestack structurally constrained impedance inversion

Geophysics ◽  
2018 ◽  
Vol 83 (2) ◽  
pp. R89-R103 ◽  
Author(s):  
Haitham Hamid ◽  
Adam Pidlisecky ◽  
Larry Lines
Keyword(s):  
Seismic Data ◽  
Local Structure ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Simultaneous Inversion ◽  
Common Depth Point ◽  
Inversion Methods ◽  
Impedance Inversion ◽  
Regularization Operator ◽  
Complex Geology

Classical prestack impedance inversion methods are based on performing a common-depth point (CDP) by CDP inversion using Tikhonov-type regularization. We refer to it as lateral unconstrained inversion (1D-LUI). Prestack seismic data usually have a low signal-to-noise ratio, and the 1D-LUI approach is sensitive to noise. The inversion results can be noisy and lead to an unfocused transition between vertical formation boundaries. The lateral constrained inversion (1D-LCI) can suppress the noise and provide sharp boundaries between inverted 1D models in regions where the layer dips are less than 20°. However, in complex geology, the disadvantage of using the 1D-LC approach is the lateral smearing of the steeply dipping layers. We have developed a structurally constrained inversion (1D-SCI) approach to mitigate the smearing associated with 1D-LCI. SCI involves simultaneous inversion of all seismic CDPs using a regularization operator that forces the solution to honor the local structure. The results of the 1D-SCI were superior compared with the 1D-LUI and 1D-LCI approaches. The steeply dipping layers are clearly visible on the SCI inverted results.

Phase‐coherency filtering of reflection seismic data

Geophysics ◽  
1985 ◽  
Vol 50 (9) ◽  
pp. 1505-1509 ◽  
Author(s):  
John D. McGlynn ◽  
George E. Ioup
Keyword(s):  
Seismic Data ◽  
Output Energy ◽  
Signal To Noise ◽  
Reflection Seismic ◽  
Advantages And Disadvantages ◽  
Common Depth Point ◽  
Multichannel Data ◽  
Band Pass ◽  
Standard Techniques

In addition to the standard techniques of stacking and digital band‐pass filtering for enhancing signal‐to‐noise (S/N) ratio for common‐depth‐point (CDP) reflection seismic data, a number of alternative or supplementary methods are available: (1) weighted mixing of adjacent traces, (2) semblance weighting of multichannel data based upon interchannel semblances (Neidell and Taner, 1971), and (3) filtering with the output energy filter (Robinson and Treitel, 1980). Each approach has advantages and disadvantages.

STUDY OF MULTIPLE REFLECTIONS USING A ONE‐DIMENSIONAL SEISMIC MODEL

Geophysics ◽  
1962 ◽  
Vol 27 (1) ◽  
pp. 61-72 ◽  
Author(s):  
A. D. Bennett
Keyword(s):  
Acoustic Pulse ◽  
Seismic Model ◽  
Velocity Data ◽  
Seismic Record ◽  
Multiple Reflections ◽  
One Dimensional ◽  
Well Model ◽  
Seismic Records ◽  
Acoustic Velocities ◽  
Magnetostrictive Transducer

A one‐dimensional seismic model consisting of a multisection metal rod was used in a study of multiple reflections. The model was designed from velocity data provided by an acoustic velocity log. Reflecting interfaces were introduced into the model by changing the rod diameter. An acoustic pulse simulating a shot was applied near the top of the model by a magnetostrictive transducer. Reflections were detected by a crystal receiver placed at the top of the model. Means were devised to achieve an acceptable correspondence in character between a field seismic record obtained at a well site and a synthetic record produced by the model based on acoustic velocities in the well. Model techniques were worked out to separate and identify primary and multiple reflections as an aid in the interpretation of field seismic records.

MULTICHANNEL DECONVOLUTION FILTERING OF FIELD RECORDED SEISMIC DATA

Geophysics ◽  
1968 ◽  
Vol 33 (5) ◽  
pp. 711-722 ◽  
Author(s):  
E. B. Davies ◽  
E. J. Mercado
Keyword(s):  
Seismic Data ◽  
Single Channel ◽  
Synthetic Data ◽  
Wiener Filter ◽  
Coherent Noise ◽  
Channel Output ◽  
Common Depth Point ◽  
Seismic Records ◽  
Output Characteristics ◽  
Multichannel Deconvolution

Several writers have proposed the use of multichannel filters for the elimination of coherent noise on seismic records. One filter of this type which can be constructed is a multichannel Wiener filter which has a multichannel input and a single channel output. In this form, it is applicable to data collected for vertical or horizontal common‐depth‐point stack processing. The choice of desired output characteristics for this Wiener filter is flexible and, for example, can be tuned to correspond to multichannel deconvolution. The results of the application of filters of this type to field and synthetic data, in general, show little if any advantage over single‐channel deconvolution. This failure appears to be connected with the low cross coherence of both noise and reflection signal on field‐recorded, common‐depth‐point traces.

Sign‐bit amplitude recovery with applications to seismic data

Geophysics ◽  
1982 ◽  
Vol 47 (11) ◽  
pp. 1527-1539 ◽  
Author(s):  
J. T. O’Brien ◽  
W. P. Kamp ◽  
G. M. Hoover
Keyword(s):  
Seismic Data ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Recovery Process ◽  
Signal To Noise ◽  
Common Depth Point ◽  
Seismic Recording ◽  
Noise Ratio ◽  
Correct Application ◽  
Complete Amplitude

Sign‐bit digital recording means that only the sign of the analog signal is recorded with one bit. In conventional seismic recording, 16 to 20 binary bits are acquired per sample point. The economic advantages of sign‐bit acquisition are immediately obvious. Complete amplitude recovery, comparable to full‐gain recording, can be achieved by correct application of sign‐bit techniques. We describe the amplitude recovery process in a semiintuitive manner to promote the understanding necessary for proper application of the technique. The dynamic range requirements in seismic applications are discussed. Sign‐bit digitization is a completely viable technique for recording seismic data, provided that two conditions are fulfilled. First, in real time, the coherent‐signal‐to‐randomnoise‐ratio must be ⩽1.0. Second, the data must be recorded with sufficient redundancy. Redundancy is achieved by source repetition, sweep correlation, and high‐fold common‐depth‐point stacking, usually in combination. Failure to abide by these two restrictions results in (1) incomplete amplitude recovery, i.e., clipped data, and (2) insufficient dynamic range in the recovered signal. We derive the requirement that the signal‐to‐noise ratio be less than one; we also discuss the consequences of violating that requirement, namely clipping, at various points in the processing sequence. The amount of information lost is proportional to the degree of clipping; a small amount can be tolerated. Calculated expectation values show that (subject to the requirement that the signal‐to‐noise ratio be less than 1.0) an unbiased estimator can be chosen. The variance of these estimators is approximately the same as that for full‐gain seismic techniques. With sufficient redundancy, the variance can be made as small as necessary to achieve the required dynamic range. With proper attention to these findings, sign‐bit digitized data are found to be a totally viable tool.

Surface wave attenuation of seismic records with the co-core trace transform filter

Geophysics ◽  
2011 ◽  
Vol 76 (6) ◽  
pp. V115-V128 ◽  
Author(s):  
Ning Wu ◽  
Yue Li ◽  
Baojun Yang
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Field Data ◽  
Wave Attenuation ◽  
Seismic Events ◽  
Data Sets ◽  
Transform Domain ◽  
Recent Developments ◽  
Seismic Records ◽  
Trace Transform

To remove surface waves from seismic records while preserving other seismic events of interest, we introduced a transform and a filter based on recent developments in image processing. The transform can be seen as a weighted Radon transform, in particular along linear trajectories. The weights in the transform are data dependent and designed to introduce large amplitude differences between surface waves and other events such that surface waves could be separated by a simple amplitude threshold. This is a key property of the filter and distinguishes this approach from others, such as conventional ones that use information on moveout ranges to apply a mask in the transform domain. Initial experiments with synthetic records and field data have demonstrated that, with the appropriate parameters, the proposed trace transform filter performs better both in terms of surface wave attenuation and reflected signal preservation than the conventional methods. Further experiments on larger data sets are needed to fully assess the method.

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