Near Surface Velocity Analysis in the Common Image Cube (CIC) Domain

2008 ◽  
Author(s):  
S. M. Al-Saleh ◽  
P. G. Kelamis
Keyword(s):  
Surface Velocity ◽  
Velocity Analysis ◽  
Near Surface ◽  
The Common ◽  
Image Cube

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.

Tau migration and velocity analysis: Theory and synthetic examples

Geophysics ◽  
2003 ◽  
Vol 68 (4) ◽  
pp. 1331-1339 ◽  
Author(s):  
Tariq Alkhalifah
Keyword(s):  
Time Domain ◽  
Synthetic Data ◽  
Velocity Model ◽  
Migration Velocity ◽  
Surface Velocity ◽  
Velocity Analysis ◽  
Near Surface ◽  
Prestack Migration ◽  
Interval Velocity ◽  
Migration Velocity Analysis

Prestack migration velocity analysis in the time domain reduces the velocity‐depth ambiguity usually hampering the performance of prestack depth‐migration velocity analysis. In prestack τ migration velocity analysis, we keep the interval velocity model and the output images in vertical time. This allows us to avoid placing reflectors at erroneous depths during the velocity analysis process and, thus, avoid slowing down its convergence to the true velocity model. Using a 1D velocity update scheme, the prestack τ migration velocity analysis performed well on synthetic data from a model with a complex near‐surface velocity. Accurate velocity information and images were obtained using this time‐domain method. Problems occurred only in resolving a thin layer where the low resolution and fold of the synthetic data made it practically impossible to estimate velocity accurately in this layer. This 1D approach also provided us reasonable results for synthetic data from the Marmousi model. Despite the complexity of this model, the τ domain implementation of the prestack migration velocity analysis converged to a generally reasonable result, which includes properly imaging the elusive top‐of‐the‐reservoir layer.

Near-surface scattered waves enhancement with source-receiver interferometry

Geophysics ◽  
2018 ◽  
Vol 83 (6) ◽  
pp. Q49-Q69
Author(s):  
Jixiang Xu ◽  
Shitai Dong ◽  
Huajuan Cui ◽  
Yan Zhang ◽  
Ying Hu ◽  
...  
Keyword(s):  
Seismic Data ◽  
Seismic Waves ◽  
Scattered Wave ◽  
Receiver Functions ◽  
Surface Velocity ◽  
Seismic Exploration ◽  
Common Source ◽  
Constructive Interference ◽  
Near Surface ◽  
The Common

Near-surface scattered waves (NSWs) are the main noise in seismic data in areas with a complex near surface and can be divided into surface-to-surface scattered waves and body-to-surface scattered waves. We have developed a method for NSW enhancement that uses modified source-receiver interferometry. The method consists of two parts. First, deconvolutional intersource interferometry is used to cancel the common raypath of seismic waves from a near-surface scatterer to the common receiver and the receiver function. Second, convolutional interreceiver interferometry is used to compensate the common raypath of seismic waves from the common source to the near-surface scatterer and the source function. For an isotropic point scatterer near the earth’s surface in modified source-receiver interferometry, a body-to-surface scattered wave can be reconstructed by constructive interference not only among three body-to-surface scattered waves but also among a body-to-surface scattered wave and two surface-to-surface scattered waves; a surface-to-surface scattered wave can be reconstructed by constructive interference not only among three surface-to-surface scattered waves but also among a surface-to-surface scattered wave and two body-to-surface scattered waves. According to stationary phase analysis based on the superposition principle, we have developed a so-called dual-wheel driving configuration of modified source-receiver interferometry for enhancing NSWs in the data of conventional seismic exploration. The main advantages of the scheme are that (1) it can be used to enhance NSWs without the need for any a priori knowledge of topography and near-surface velocity, (2) it can be used to reconstruct NSWs from real sources to real receivers, including 3D near-surface side-scattered waves, and (3) it can be applied to conventional seismic data with finite-frequency bandwidth, spatially limited and sparse arrays, different source and receiver functions, and static correction. Numerically simulated data and field seismic data are used to demonstrate the feasibility and effectiveness of the scheme.

Migration velocity analysis using the common image cube (CIC)

Geophysics ◽  
2011 ◽  
Vol 76 (5) ◽  
pp. WB127-WB134 ◽  
Author(s):  
Saleh M. Al-Saleh ◽  
Jianwu Jiao ◽  
Adam J. Fox
Keyword(s):  
Green's Functions ◽  
Cross Correlation ◽  
Green’S Functions ◽  
Velocity Model ◽  
Migration Velocity ◽  
Velocity Analysis ◽  
Image Domain ◽  
Migration Velocity Analysis ◽  
The Common ◽  
Image Cube

Migration velocity analysis (MVA) is commonly performed in the image domain in conjunction with ray-based tomography to update the velocity model. This approach can be challenging in the presence of large velocity errors as it may require many MVA iterations before converging to a model that can focus the events in the image domain. We introduced a downward continuation-based domain for carrying out MVA that is more flexible than conventional domains. This approach consists of two steps: (1) forming the common image cube (CIC) and (2) modeling the Green’s functions. In the first step, the cross-correlation imaging condition is relaxed to produce more than the zero lag common image gather (CIG). Slicing these data at different lags forms a series of CIGs, whereas a conventional CIG can be obtained by slicing the cube at the zero lag. When the velocity model used for the migration differs from the true velocity model, properly flattened events may occur in CIGs other than the zero lag. In the second step, for each event on the CIG, we picked the cross-correlation lag and depth at which it flattens best. For each event, we modeled a Green’s function by seeding a source at the focusing depth using one-way wave-equation modeling. This process is then repeated for other events at different lateral positions. The result is a set of Green’s functions whose wavefield approximates the ones that would have been generated if the correct velocity model was used to simulate these gathers. The updated Green functions are easier to work with than the raw data as they have less noise. Wavefield tomography can then be applied on these data-driven, modeled Green’s functions to build the final velocity model. Tests on synthetic and real 2D data confirm the method’s effectiveness in building velocity models in complex structural areas with large lateral velocity variations.

Near-surface and anisotropy modeling for efficient land seismic depth imaging in low-relief geology

2017 ◽  
Vol 5 (4) ◽  
pp. SR1-SR12 ◽  
Author(s):  
Daniele Colombo ◽  
Ernesto Sandoval-Curiel ◽  
Mats Ris ◽  
Salvarajah Seeni
Keyword(s):  
Joint Inversion ◽  
Surface Velocity ◽  
Accurate Estimation ◽  
Earth Model ◽  
Velocity Analysis ◽  
Near Surface ◽  
Depth Imaging ◽  
Long Wavelength ◽  
Transient Electromagnetic ◽  
Seismic Image

Prestack depth migration of land data presents unique characteristics and challenges that distinguish it from the workflows applied for marine data. Such unique characteristics are primarily related to the near surface. In areas of low-relief geology, near-surface velocity variations can obscure the reservoir structure. The remaining deeper earth model section has good lateral continuity and can be described effectively by smooth velocity fields. Strategies for estimating the near-surface effects and incorporating them into a processing workflow are of primary importance for the successful depth imaging of land seismic data. The second important aspect of a depth imaging workflow is that the seismic image must honor the well markers or formation tops. The subhorizontal fine-scale layering of low-relief structures can cause anisotropy that needs to be taken into account to achieve accurate well ties and good image quality. We have evaluated the application of an efficient workflow to achieve fast and reliable depth imaging in layered geology; this involves the decomposition of the near-surface velocity into short-, medium-, and long-wavelength terms followed by reflection velocity analysis and anisotropic parameter scanning. The long-wavelength components are solved by dynamic velocity analysis, whereas the medium- and short-wavelength terms are evaluated by surface-consistent analysis applied to refracted and reflected data. Interaction with seismic interpreters and geology-consistent updates mitigates the possibility of introducing errors in areas not covered by wells. The workflow is applied to a structure-controlled wadi in central Saudi Arabia showing complex near-surface conditions and imaging problems. The study incorporates high-resolution helicopter-borne transient electromagnetic data that are used to constrain seismic traveltime inversion through cross-gradient structural regularization (joint inversion). Fast and robust depth imaging constrained by well data is obtained through accurate estimation of near-surface velocities, anisotropy, and geology-consistent analysis.

scholarly journals Physics-Based Relationship for Pore Pressure and Vertical Stress Monitoring Using Seismic Velocity Variations

2021 ◽  
Vol 13 (14) ◽  
pp. 2684
Author(s):  
Eldert Fokker ◽  
Elmer Ruigrok ◽  
Rhys Hawkins ◽  
Jeannot Trampert
Keyword(s):  
Pore Pressure ◽  
Seismic Velocity ◽  
Pressure Head ◽  
Groundwater Table ◽  
Surface Velocity ◽  
Seismic Velocities ◽  
Stress Monitoring ◽  
Near Surface ◽  
Velocity Variations ◽  
Velocity Changes

Previous studies examining the relationship between the groundwater table and seismic velocities have been guided by empirical relationships only. Here, we develop a physics-based model relating fluctuations in groundwater table and pore pressure with seismic velocity variations through changes in effective stress. This model justifies the use of seismic velocity variations for monitoring of the pore pressure. Using a subset of the Groningen seismic network, near-surface velocity changes are estimated over a four-year period, using passive image interferometry. The same velocity changes are predicted by applying the newly derived theory to pressure-head recordings. It is demonstrated that the theory provides a close match of the observed seismic velocity changes.

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