scholarly journals Recursive prestack depth migration using CFP gathers

Geophysics ◽  
2006 ◽  
Vol 71 (6) ◽  
pp. S273-S283 ◽  
Author(s):  
Jan Thorbecke ◽  
A. J. Berkhout
Keyword(s):  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Velocity Analysis ◽  
Signal To Noise ◽  
Depth Migration ◽  
Prestack Migration ◽  
Data Volume ◽  
The Common ◽  
Complex Geology ◽  
Focus Point

The common-focus-point technology (CFP) describes prestack migration by focusing in two steps: emission and detection. The output of the first focusing step represents a CFP gather. This gather defines a shot record that represents the subsurface response resulting from a focused source wavefield. We propose applying the recursive shot-record, depth-migration algorithm to the CFP gathers of a seismic data volume and refer to this process as CFP-gather migration. In the situation of complex geology and/or low signal-to-noise ratio, CFP-based image gathers are easier to interpret for nonalignment than the conventional image gathers. This makes the CFP-based image gathers better suited for velocity analysis. This important property is illustrated by examples on the Marmousi model.

Prestack Kirchhoff depth migration of shallow seismic data

Geophysics ◽  
1998 ◽  
Vol 63 (4) ◽  
pp. 1241-1247 ◽  
Author(s):  
Linus Pasasa ◽  
Friedemann Wenzel ◽  
Ping Zhao
Keyword(s):  
Waste Disposal ◽  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Disposal Site ◽  
Model Estimation ◽  
Waste Disposal Site ◽  
Depth Migration ◽  
Prestack Migration ◽  
Shallow Seismic ◽  
Kirchhoff Depth Migration

Prestack Kirchhoff depth migration is applied successfully to shallow seismic data from a waste disposal site near Arnstadt in Thuringia, Germany. The motivation behind this study was to locate an underground building buried in a waste disposal. The processing sequence of the prestack migration is simplified significantly as compared to standard common (CMP) data processing. It includes only two parts: (1) velocity‐depth‐model estimation and (2) prestack depth migration. In contrast to conventional CMP stacking, prestack migration does not require a separation of reflections and refractions in the shot data. It still provides an appropriate image. Our data example shows that a superior image can be achieved that would contain not just subtle improvements but a qualitative step forward in resolution and signal‐to‐noise ratio.

scholarly journals Study on the Velocity Analysis Method of Low SNR Seismic Data

2021 ◽  
Vol 11 (1) ◽  
pp. 78
Author(s):  
Jianbo He ◽  
Zhenyu Wang ◽  
Mingdong Zhang
Keyword(s):  
Seismic Data ◽  
Fresnel Zone ◽  
Signal To Noise Ratio ◽  
Normal Wave ◽  
Curvature Radius ◽  
Velocity Spectrum ◽  
Velocity Analysis ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Zero Offset

When the signal to noise ratio of seismic data is very low, velocity spectrum focusing will be poor., the velocity model obtained by conventional velocity analysis methods is not accurate enough, which results in inaccurate migration. For the low signal noise ratio (SNR) data, this paper proposes to use partial Common Reflection Surface (CRS) stack to build CRS gathers, making full use of all of the reflection information of the first Fresnel zone, and improves the signal to noise ratio of pre-stack gathers by increasing the number of folds. In consideration of the CRS parameters of the zero-offset rays emitted angle and normal wave front curvature radius are searched on zero offset profile, we use ellipse evolving stacking to improve the zero offset section quality, in order to improve the reliability of CRS parameters. After CRS gathers are obtained, we use principal component analysis (PCA) approach to do velocity analysis, which improves the noise immunity of velocity analysis. Models and actual data results demonstrate the effectiveness of this method.

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.

Prestack seismic data enhancement with partial common-reflection-surface (CRS) stack

Geophysics ◽  
2009 ◽  
Vol 74 (3) ◽  
pp. V49-V58 ◽  
Author(s):  
Mikhail Baykulov ◽  
Dirk Gajewski
Keyword(s):  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Synthetic Data ◽  
Original Data ◽  
Signal To Noise ◽  
Prestack Depth Migration ◽  
Depth Migration ◽  
Common Reflection Surface ◽  
Noise Ratio

We developed a new partial common-reflection-surface (CRS) stacking method to enhance the quality of sparse low-fold seismic data. For this purpose, we use kinematic wavefield attributes computed during the automatic CRS stack. We apply a multiparameter CRS traveltime formula to compute partial stacked CRS supergathers. Our algorithm allows us to generate NMO-uncorrected gathers without the application of inverse NMO/DMO. Gathers obtained by this approach are regularized and have better signal-to-noise ratio compared with original common-midpoint gathers. Instead of the original data, these improved prestack data can be used in many conventional processing steps, e.g., velocity analysis or prestack depth migration, providing enhanced images and better quality control. We verified the method on 2D synthetic data and applied it to low-fold land data from northern Germany. The synthetic examples show the robustness of the partial CRS stack in the presence of noise. Sparse land data became regularized, and the signal-to-noise ratio of the seismograms increased as a result of the partial CRS stack. Prestack depth migration of the generated partially stacked CRS supergathers produced significantly improved common-image gathers as well as depth-migrated sections.

A two‐pass approximation to 3-D prestack migration

Geophysics ◽  
1996 ◽  
Vol 61 (2) ◽  
pp. 409-421 ◽  
Author(s):  
Anat Canning ◽  
Gerald H. F. Gardner
Keyword(s):  
Computation Time ◽  
Three Dimensions ◽  
Velocity Analysis ◽  
Depth Migration ◽  
Prestack Migration ◽  
Time Migration ◽  
Data Volume ◽  
Land Survey ◽  
Zero Offset ◽  
The One

A two‐pass approximation to 3-D Kirchhoff migration simplifies the migration procedure by reducing it to a succession of 2-D operations. This approach has proven very successful in the zero‐offset case. A two‐pass approximation to 3-D migration is described here for the prestack case. Compared to the one‐pass approach, the scheme presented here provides significant reduction in computation time and a relatively simple data manipulation scheme. The two‐pass method was designed using velocity independent prestack time migration (DMO‐PSI) applied in the crossline direction, followed by conventional prestack depth migration in the inline direction. Velocity analysis, an important part of prestack migration, is also included in the two‐pass scheme. It is carried out as a 2-D procedure after 3-D effects are removed from the data volume. The procedure presented here is a practical full volume 3-D prestack migration. One of its main benefits is a realistic and efficient iterative velocity analysis procedure in three dimensions. The algorithm was designed in the frequency domain and the computational scheme was optimized by processing individual frequency slices independently. Irregular trace distribution, a feature that characterizes most 3-D seismic surveys, is implicitly accounted for within the two‐pass algorithm. A numerical example tests the performance of the two‐pass 3-D prestack migration program in the presence of a vertical velocity gradient. A 3-D land survey from a fold and thrust belt region was used to demonstrate the algorithm in a complex geological setting. The results were compared with images from other 2-D and 3-D migration schemes and show improved resolution and higher signal content.

Innovative Seismic Data Processing Approach to Improve Signal to Noise Ratio

2001 ◽  
Author(s):  
P.P. Gupta ◽  
Kuldeep Prakash ◽  
Paramjeet Singh ◽  
M.N. Lakra
Keyword(s):  
Data Processing ◽  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Seismic Data Processing ◽  
Signal To Noise ◽  
Processing Approach ◽  
Noise Ratio
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