Removing fault shadow distortions from seismic images using depth-velocity modelling and pre-stack depth migration

2012 ◽  
Vol 52 (2) ◽  
pp. 700
Author(s):  
Sergey Birdus ◽  
Alexey Artyomov
Keyword(s):  
Real Data ◽  
Velocity Model ◽  
Velocity Inversion ◽  
Depth Migration ◽  
Velocity Models ◽  
Depth Processing ◽  
Different Types ◽  
Successful Removal ◽  
Velocity Anomalies ◽  
Additional Image

In many areas, fault shadows manifest a serious challenge to seismic imaging. The major part of this problem is caused by different types of velocity variations caused by faults. Pre-stack depth migration with sufficiently accurate velocity model successfully resolves this problem and the high resolution tomographic depth-velocity modelling is the most important component of the solution. During depth processing on a number of real 3D seismic datasets with fault shadows from Australia and other regions, the following were noticed: The appearance of the image distortions below the faults and the convergence speed of the tomographic velocity inversion depend on the acquisition direction. Sometimes, tomographic modelling produces depth-velocity models that closely follow geology, but the models contain non-geological looking anomalies in other areas. In both cases, the depth migration delivers distortion-free images. If anisotropy is present in faulted areas, it creates additional image distortions and can require extra input data and processing efforts. To examine these effects and optimise depth-processing workflow, several 3D synthetic seismic datasets were created for different types of velocity anomalies associated with the faults in isotropic and anisotropic media and different acquisition directions. On synthetic and real data from Australia, different types of fault shadows are illustrated; how they can be solved depending on the acquisition direction are also shown. Some types of the fault shadows are shown to require multi-azimuth illumination to guarantee their successful removal.

Kinematic interpretation in the prestack depth‐migrated domain

Geophysics ◽  
1997 ◽  
Vol 62 (4) ◽  
pp. 1226-1237 ◽  
Author(s):  
Irina Apostoiu‐Marin ◽  
Andreas Ehinger
Keyword(s):  
Signal To Noise Ratio ◽  
Velocity Model ◽  
Point Of View ◽  
Prestack Depth Migration ◽  
Depth Migration ◽  
Velocity Models ◽  
Time Domain Data ◽  
And Migration ◽  
Point To Point ◽  
Homogeneous Media

Prestack depth migration can be used in the velocity model estimation process if one succeeds in interpreting depth events obtained with erroneous velocity models. The interpretational difficulty arises from the fact that migration with erroneous velocity does not yield the geologically correct reflector geometries and that individual migrated images suffer from poor signal‐to‐noise ratio. Moreover, migrated events may be of considerable complexity and thus hard to identify. In this paper, we examine the influence of wrong velocity models on the output of prestack depth migration in the case of straight reflector and point diffractor data in homogeneous media. To avoid obscuring migration results by artifacts (“smiles”), we use a geometrical technique for modeling and migration yielding a point‐to‐point map from time‐domain data to depth‐domain data. We discover that strong deformation of migrated events may occur even in situations of simple structures and small velocity errors. From a kinematical point of view, we compare the results of common‐shot and common‐offset migration. and we find that common‐offset migration with erroneous velocity models yields less severe image distortion than common‐shot migration. However, for any kind of migration, it is important to use the entire cube of migrated data to consistently interpret in the prestack depth‐migrated domain.

Migration velocity analysis based on focusing diffractions generated using the CRS wavefront attributes: Application to real land data

Geophysics ◽  
2021 ◽  
pp. 1-50
Author(s):  
German Garabito ◽  
José Silas dos Santos Silva ◽  
Williams Lima
Keyword(s):  
Time Domain ◽  
Real Data ◽  
Normal Incidence ◽  
Velocity Model ◽  
Migration Velocity ◽  
Velocity Analysis ◽  
Velocity Models ◽  
Time Migration ◽  
Migration Velocity Analysis ◽  
The Time Domain

In land seismic data processing, the prestack time migration (PSTM) image remains the standard imaging output, but a reliable migrated image of the subsurface depends on the accuracy of the migration velocity model. We have adopted two new algorithms for time-domain migration velocity analysis based on wavefield attributes of the common-reflection-surface (CRS) stack method. These attributes, extracted from multicoverage data, were successfully applied to build the velocity model in the depth domain through tomographic inversion of the normal-incidence-point (NIP) wave. However, there is no practical and reliable method for determining an accurate and geologically consistent time-migration velocity model from these CRS attributes. We introduce an interactive method to determine the migration velocity model in the time domain based on the application of NIP wave attributes and the CRS stacking operator for diffractions, to generate synthetic diffractions on the reflection events of the zero-offset (ZO) CRS stacked section. In the ZO data with diffractions, the poststack time migration (post-STM) is applied with a set of constant velocities, and the migration velocities are then selected through a focusing analysis of the simulated diffractions. We also introduce an algorithm to automatically calculate the migration velocity model from the CRS attributes picked for the main reflection events in the ZO data. We determine the precision of our diffraction focusing velocity analysis and the automatic velocity calculation algorithms using two synthetic models. We also applied them to real 2D land data with low quality and low fold to estimate the time-domain migration velocity model. The velocity models obtained through our methods were validated by applying them in the Kirchhoff PSTM of real data, in which the velocity model from the diffraction focusing analysis provided significant improvements in the quality of the migrated image compared to the legacy image and to the migrated image obtained using the automatically calculated velocity model.

Velocity inversion by global optimization using finite-offset common-reflection-surface stacking applied to synthetic and Tacutu Basin seismic data

Geophysics ◽  
2019 ◽  
Vol 84 (2) ◽  
pp. R165-R174 ◽  
Author(s):  
Marcelo Jorge Luz Mesquita ◽  
João Carlos Ribeiro Cruz ◽  
German Garabito Callapino
Keyword(s):  
Objective Function ◽  
Real Data ◽  
Velocity Model ◽  
Data Sets ◽  
Layer By Layer ◽  
Velocity Inversion ◽  
Very Fast Simulated Annealing ◽  
Target Layer ◽  
Common Reflection Surface ◽  
The Mean

Estimation of an accurate velocity macromodel is an important step in seismic imaging. We have developed an approach based on coherence measurements and finite-offset (FO) beam stacking. The algorithm is an FO common-reflection-surface tomography, which aims to determine the best layered depth-velocity model by finding the model that maximizes a semblance objective function calculated from the amplitudes in common-midpoint (CMP) gathers stacked over a predetermined aperture. We develop the subsurface velocity model with a stack of layers separated by smooth interfaces. The algorithm is applied layer by layer from the top downward in four steps per layer. First, by automatic or manual picking, we estimate the reflection times of events that describe the interfaces in a time-migrated section. Second, we convert these times to depth using the velocity model via application of Dix’s formula and the image rays to the events. Third, by using ray tracing, we calculate kinematic parameters along the central ray and build a paraxial FO traveltime approximation for the FO common-reflection-surface method. Finally, starting from CMP gathers, we calculate the semblance of the selected events using this paraxial traveltime approximation. After repeating this algorithm for all selected CMP gathers, we use the mean semblance values as an objective function for the target layer. When this coherence measure is maximized, the model is accepted and the process is completed. Otherwise, the process restarts from step two with the updated velocity model. Because the inverse problem we are solving is nonlinear, we use very fast simulated annealing to search the velocity parameters in the target layers. We test the method on synthetic and real data sets to study its use and advantages.

Migration moveout analysis and depth focusing

Geophysics ◽  
1993 ◽  
Vol 58 (1) ◽  
pp. 91-100 ◽  
Author(s):  
Claude F. Lafond ◽  
Alan R. Levander
Keyword(s):  
Heterogeneous Media ◽  
A Priori ◽  
Complex Structure ◽  
Tomographic Reconstruction ◽  
Synthetic Data ◽  
Real Data ◽  
Velocity Model ◽  
Velocity Analysis ◽  
Data Set ◽  
Velocity Models

Prestack depth migration still suffers from the problems associated with building appropriate velocity models. The two main after‐migration, before‐stack velocity analysis techniques currently used, depth focusing and residual moveout correction, have found good use in many applications but have also shown their limitations in the case of very complex structures. To address this issue, we have extended the residual moveout analysis technique to the general case of heterogeneous velocity fields and steep dips, while keeping the algorithm robust enough to be of practical use on real data. Our method is not based on analytic expressions for the moveouts and requires no a priori knowledge of the model, but instead uses geometrical ray tracing in heterogeneous media, layer‐stripping migration, and local wavefront analysis to compute residual velocity corrections. These corrections are back projected into the velocity model along raypaths in a way that is similar to tomographic reconstruction. While this approach is more general than existing migration velocity analysis implementations, it is also much more computer intensive and is best used locally around a particularly complex structure. We demonstrate the technique using synthetic data from a model with strong velocity gradients and then apply it to a marine data set to improve the positioning of a major fault.

The application of 3-D depth migration to the development of an Alaskan offshore oil field

Geophysics ◽  
1994 ◽  
Vol 59 (10) ◽  
pp. 1551-1560 ◽  
Author(s):  
David N. Whitcombe ◽  
Eugene H. Murray ◽  
Laurie A. St. Aubin ◽  
Randall J. Carroll
Keyword(s):  
Velocity Model ◽  
Oil Field ◽  
Northwestern Part ◽  
Positioning Error ◽  
Depth Migration ◽  
Velocity Models ◽  
Positioning Errors ◽  
Ray Trace ◽  
Offshore Oil ◽  
Lateral Positioning

Inconsistencies in fault positioning between overlapping 3-D seismic surveys over the northwestern part of the Endicott Field highlighted lateral positioning errors of the order of 1000 ft (330 m) in the seismic images. This large uncertainty in fault positioning placed a high and often unacceptable risk on the placement of wells. To quantify and correct for the seismic positioning error, 3-D velocity models were developed for ray‐trace modeling. The lateral positioning error maps produced revealed significant variation in the mispositioning within the Endicott Field that were mainly caused by lateral variations in permafrost thickness. These maps have been used to correct the positions of mapped features and have enabled several wells to be successfully placed close to major faults. Prior to this analysis, these wells were considered too risky to place optimally. The seismic data were 3-D poststack depth migrated with the final velocity model, producing a repositioned image that was consistent with the ray‐trace predictions. Additionally, a general enhancement of data imaging improved the interpretability and enabled the remapping and subsequent successful development of the peripheral Sag Delta North accumulation.

Noise removal by migration of time-shift images

Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. S105-S111 ◽  
Author(s):  
Sheng Xu ◽  
Feng Chen ◽  
Bing Tang ◽  
Gilles Lambare
Keyword(s):  
Time Lag ◽  
Real Data ◽  
Velocity Model ◽  
Noise Removal ◽  
Time Shift ◽  
Reverse Time ◽  
Coherent Noise ◽  
Data Set ◽  
Depth Migration ◽  
Time Migration

When using seismic data to image complex structures, the reverse time migration (RTM) algorithm generally provides the best results when the velocity model is accurate. With an inexact model, moveouts appear in common image gathers (CIGs), which are either in the surface offset domain or in subsurface angle domain; thus, the stacked image is not well focused. In extended image gathers, the strongest energy of a seismic event may occur at non-zero-lag in time-shift or offset-shift gathers. Based on the operation of RTM images produced by the time-shift imaging condition, the non-zero-lag time-shift images exhibit a spatial shift; we propose an approach to correct them by a second pass of migration similar to zero-offset depth migration; the proposed approach is based on the local poststack depth migration assumption. After the proposed second-pass migration, the time-shift CIGs appear to be flat and can be stacked. The stack enhances the energy of seismic events that are defocused at zero time lag due to the inaccuracy of the model, even though the new focused events stay at the previous positions, which might deviate from the true positions of seismic reflection. With the stack, our proposed approach is also able to attenuate the long-wavelength RTM artifacts. In the case of tilted transverse isotropic migration, we propose a scheme to defocus the coherent noise, such as migration artifacts from residual multiples, by applying the original migration velocity model along the symmetry axis but with different anisotropic parameters in the second pass of migration. We demonstrate that our approach is effective to attenuate the coherent noise at subsalt area with two synthetic data sets and one real data set from the Gulf of Mexico.

scholarly journals Study on the limitations of traveltime inversion in the presence of extreme velocity anomalies

2013 ◽  
Vol 5 (1) ◽  
pp. 189-226
Author(s):  
I. Flecha ◽  
R. Carbonell ◽  
R. W. Hobbs
Keyword(s):  
Oil Industry ◽  
Velocity Model ◽  
Wide Angle ◽  
Seismic Reflection Data ◽  
Traveltime Inversion ◽  
Additional Information ◽  
Velocity Models ◽  
Reflection Data ◽  
Velocity Anomalies ◽  
Tomographic Inversions

Abstract. The difficulties of seismic imaging beneath high velocity structures are widely recognised. In this setting, theoretical analysis of synthetic wide-angle seismic reflection data indicates that velocity models are not well constrained. A two-dimensional velocity model was built to simulate a simplified structural geometry given by a basaltic wedge placed within a sedimentary sequence. This model reproduces the geological setting in areas of special interest for the oil industry as the Faroe-Shetland Basin. A wide-angle synthetic dataset was calculated on this model using an elastic finite difference scheme. This dataset provided travel times for tomographic inversions. Results show that the original model can not be completely resolved without considering additional information. The resolution of nonlinear inversions lacks a functional mathematical relationship, therefore, statistical approaches are required. Stochastical tests based on Metropolis techniques support the need of additional information to properly resolve subbasalt structures.

Optimization and sensitivity analysis of seismic depth migrations from Hibernia Field

Geophysics ◽  
1998 ◽  
Vol 63 (6) ◽  
pp. 2054-2062 ◽  
Author(s):  
Irene Kelly ◽  
Larry R. Lines
Keyword(s):  
Sensitivity Analysis ◽  
Least Squares ◽  
Real Data ◽  
Optimization Method ◽  
Velocity Estimation ◽  
Inversion Method ◽  
Depth Migration ◽  
Velocity Models ◽  
Sensitivity Analysis Method ◽  
Seismic Reflectors

Accurate imaging of seismic reflectors with depth migration requires accurate velocity models. In frontier areas with few well constraints, velocity estimation generally involves the use of methods such as normal moveout analysis, seismic traveltime tomography, or iterative prestack depth migration. These techniques can be effective, but may also be expensive or time‐consuming. In situations where we have information on formation tops from a series of wells which intersect seismic reflectors, we use a least‐squares optimization method to estimate velocity models. This method produces velocity models that optimize depth migrations in terms of well constraints by using least‐squares inversion to match the depth migration images to formation tops. The well log information is used to optimize poststack migration, thereby eliminating some of the time and expense of velocity analysis. In addition to applying an inversion method which optimizes depth migration in terms of formation tops, we can use a sensitivity analysis method of “most‐squares inversion” to explore a range of velocity models which provide mathematically acceptable solutions. This sensitivity analysis quantifies the expected result that our velocity estimates are generally less reliable for thin beds than for thick beds. The proposed optimization method is shown to be successful on synthetic and real data cases from the Hibernia Field of offshore Newfoundland.

Incorporating geologic information into reflection tomography

Geophysics ◽  
2004 ◽  
Vol 69 (2) ◽  
pp. 533-546 ◽  
Author(s):  
Robert G. Clapp ◽  
Biondo L. Biondi ◽  
Jon F. Claerbout
Keyword(s):  
Velocity Structure ◽  
Null Space ◽  
Velocity Model ◽  
Prestack Depth Migration ◽  
Depth Migration ◽  
Interval Velocity ◽  
Velocity Models ◽  
Regularized Inversion ◽  
Symmetric Operators ◽  
Reflection Tomography

In areas of complex geology, prestack depth migration is often necessary if we are to produce an accurate image of the subsurface. Prestack depth migration requires an accurate interval velocity model. With few exceptions, the subsurface velocities are not known beforehand and should be estimated. When the velocity structure is complex, with significant lateral variations, reflection‐tomography methods are often an effective tool for improving the velocity estimate. Unfortunately, reflection tomography often converges slowly, to a model that is geologically unreasonable, or it does not converge at all. The large null space of reflection‐tomography problems often forces us to add a sparse parameterization of the model and/or regularization criteria to the estimation. Standard tomography schemes tend to create isotropic features in velocity models that are inconsistent with geology. These isotropic features result, in large part, from using symmetric regularization operators or from choosing a poor model parameterization. If we replace the symmetric operators with nonstationary operators that tend to spread information along structural dips, the tomography will produce velocity models that are geologically more reasonable. In addition, by forming the operators in helical 1D space and performing polynomial division, we apply the inverse of these space‐varying anisotropic operators. The inverse operators can be used as a preconditioner to a standard tomography problem, thereby significantly improving the speed of convergence compared with the typical regularized inversion problem. Results from 2D synthetic and 2D field data are shown. In each case, the velocity obtained improves the focusing of the migrated image.

Practical aspects and applications of 2D stereotomography

Geophysics ◽  
2003 ◽  
Vol 68 (3) ◽  
pp. 1008-1021 ◽  
Author(s):  
Frederic Billette ◽  
Soazig Le Bégat ◽  
Pascal Podvin ◽  
Gilles Lambaré
Keyword(s):  
Estimation Method ◽  
Synthetic Data ◽  
Velocity Model ◽  
Velocity Estimation ◽  
Common Source ◽  
Depth Migration ◽  
Reflection Seismic ◽  
Velocity Models ◽  
Automatic Picking ◽  
Iterative Inversion

Stereotomography is a new velocity estimation method. This tomographic approach aims at retrieving subsurface velocities from prestack seismic data. In addition to traveltimes, the slope of locally coherent events are picked simultaneously in common offset, common source, common receiver, and common midpoint gathers. As the picking is realized on locally coherent events, they do not need to be interpreted in terms of reflection on given interfaces, but may represent diffractions or reflections from anywhere in the image. In the high‐frequency approximation, each one of these events corresponds to a ray trajectory in the subsurface. Stereotomography consists of picking and analyzing these events to update both the associated ray paths and velocity model. In this paper, we describe the implementation of two critical features needed to put stereotomography into practice: an automatic picking tool and a robust multiscale iterative inversion technique. Applications to 2D reflection seismic are presented on synthetic data and on a 2D line extracted from a 3D towed streamer survey shot in West Africa for TotalFinaElf. The examples demonstrate that the method requires only minor human intervention and rapidly converges to a geologically plausible velocity model in these two very different and complex velocity regimes. The quality of the velocity models is verified by prestack depth migration results.

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