Seismic modeling and expression of common fold-thrust structures

2020 ◽  
Vol 8 (1) ◽  
pp. T55-T65
Author(s):  
Jianjun Li ◽  
Shankar Mitra
Keyword(s):  
Velocity Model ◽  
Fault Geometry ◽  
Seismic Modeling ◽  
Fault Propagation ◽  
Lateral Velocity ◽  
Slip Ratio ◽  
Velocity Models ◽  
Time Migration ◽  
The Common

We have conducted seismic modeling of common fold-thrust structures to understand the common geologic parameters influencing seismic data and to understand the common pitfalls associated with interpreting prestack time migration (PSTM) and prestack depth migration (PSDM) data. Mode 1 fault-bend folds are generally well-imaged in PSTM data, provided the correct migration velocities are used for the dipping back and front limbs. Seismic pull-ups of the footwall related to lateral velocity variations can result in problems in interpreting the fault geometry and the subthrust area underlying the crest. Fault-tip fault-propagation folds also show significant footwall pull-ups and show poor to no imaging of the steep front limbs. The geometry of trishear fault-propagation folds is dependent on the maximum slip on the fault (S) and the fault propagation to slip ratio (P/S ratio). We found that the slip has a strong influence on the dip of the front limb and therefore the quality of imaging whereas the P/S ratio, which controls the degree of folding versus thrust faulting, has only a secondary effect. For the front limb, only the area near the synclinal axial plan is well-imaged, so that the fault geometry and extent of propagation are typically difficult to interpret. The front limb dips are also sensitive to the accuracy of the rms velocity model used for migration. Lower velocities result in steeper dipping reflectors, whereas higher velocities result in shallower dips. In general, PSDM provides better imaging of the structures; however, the accuracy and quality of the image are dependent on the velocity models and interpretation derived from the PSTM data.

Ray-based seismic modeling of geologic models: Understanding and analyzing seismic images efficiently

2015 ◽  
Vol 3 (4) ◽  
pp. SAC71-SAC89 ◽  
Author(s):  
Isabelle Lecomte ◽  
Paul Lubrano Lavadera ◽  
Ingrid Anell ◽  
Simon J. Buckley ◽  
Daniel W. Schmid ◽  
...  
Keyword(s):  
Normal Incidence ◽  
Velocity Model ◽  
Convolution Operators ◽  
Seismic Modeling ◽  
Lateral Velocity ◽  
Velocity Models ◽  
Convolution Model ◽  
Seismic Sections ◽  
Efficient Option ◽  
Ray Methods

Often, interpreters only have access to seismic sections and, at times, well data, when making an interpretation of structures and depositional features in the subsurface. The validity of the final interpretation is based on how well the seismic data are able to reproduce the actual geology, and seismic modeling can help constrain that. Ideally, modeling should create complete seismograms, which is often best achieved by finite-difference modeling with postprocessing to produce synthetic seismic sections for comparison purposes. Such extensive modeling is, however, not routinely affordable. A far more efficient option, using the simpler 1D convolution model with reflectivity logs extracted along verticals in velocity models, generates poor modeling results when lateral velocity variations are expected. A third and intermediate option is to use the various ray-based approaches available, which are efficient and flexible. However, standard ray methods, such as the normal-incidence point for unmigrated poststack sections or image rays for simulating time-migrated poststack results, cannot deal with complex and detailed targets, and will not reproduce the realistic (3D) resolution effects of seismic imaging. Nevertheless, ray methods can also be used to estimate 3D spatial prestack convolution operators, so-called point-spread functions. These are functions of the survey, velocity model, and wavelet, among others, and therefore they include 3D angle-dependent illumination and resolution effects. Prestack depth migration images are thus rapidly simulated by spatial convolution with detailed 3D reflectivity models, which goes far beyond the limits of 1D convolution modeling. This 3D convolution modeling should allow geologists to better assess their interpretations and draw more definitive conclusions.

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.

Time-migration velocity analysis by image-wave propagation of common-image gathers

Geophysics ◽  
2008 ◽  
Vol 73 (5) ◽  
pp. VE161-VE171 ◽  
Author(s):  
J. Schleicher ◽  
J. C. Costa ◽  
A. Novais
Keyword(s):  
Wave Propagation ◽  
Seismic Event ◽  
Velocity Model ◽  
Migration Velocity ◽  
Velocity Analysis ◽  
Reference Velocity ◽  
Time Migration ◽  
Migration Velocity Analysis ◽  
Velocity Image ◽  
The Common

Image-wave propagation or velocity continuation describes the variation of the migrated position of a seismic event as a function of migration velocity. Image-wave propagation in the common-image gather (CIG) domain can be combined with residual-moveout analysis for iterative migration velocity analysis (MVA). Velocity continuation of CIGs leads to a detection of those velocities in which events flatten. Although image-wave continuation is based on the assumption of a constant migration velocity, the procedure can be applied in inhomogeneous media. For this purpose, CIGs obtained by migration with an inhomogeneous macrovelocity model are continued starting from a constant reference velocity. The interpretation of continued CIGs, as if they were obtained from residual migrations, leads to a correction formula that translates residual flattening velocities into absolute time-migration velocities. In this way, the migration velocity model can be improved iteratively until a satisfactory result is reached. With a numerical example, we found that MVA with iterative image continuation applied exclusively to selected CIGs can construct a reasonable migration velocity model from scratch, without the need to build an initial model from a previous conventional normal-moveout/dip-moveout velocity analysis.

Kinematics of common-image gathers — Part 1: Theory

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. S437-S447 ◽  
Author(s):  
Jean-Philippe Montel ◽  
Gilles Lambaré
Keyword(s):  
Velocity Model ◽  
General Assumption ◽  
Azimuth Angle ◽  
Velocity Analysis ◽  
Migration Process ◽  
Kinematic Behavior ◽  
Migration Velocity Analysis ◽  
Model Update ◽  
The Common

Common-image gathers are a useful output of the migration process. Their kinematic behavior (i.e., the way they curve up or down) is an indicator of the quality of the velocity model used for migration. Traditionally, when used for migration velocity analysis, we pick structural dips in the common attribute panels (offset, angle, etc.) and residual moveout (RMO) in the gathers. The measured RMO will then tell us how much we need to update the velocity model to improve the gather’s flatness. Understanding the kinematics of the picked events is the key to an accurate model update. This point has been widely underestimated in many cases. For example, when dealing with angle gathers, there is a general assumption that the associated tomographic rays are fully defined by the picked structural dips and the gather opening and azimuth angle, and that if the velocity model is correctly updated down to a given horizon, it is not necessary to shoot the tomographic rays upward through this horizon. We find through an original theoretical analysis that both of these assumptions have to be modified when the gathers exhibit RMO. Using a kinematic analysis, we determine that knowledge of the RMO slopes is necessary to compute the tomographic rays.

scholarly journals Moving from 1-D to 3-D velocity model: automated waveform-based earthquake moment tensor inversion in the Los Angeles region

2019 ◽  
Vol 220 (1) ◽  
pp. 218-234 ◽  
Author(s):  
Xin Wang ◽  
Zhongwen Zhan
Keyword(s):  
Los Angeles ◽  
Moment Tensor ◽  
Velocity Model ◽  
Primary Control ◽  
Lateral Velocity ◽  
Real Time System ◽  
Moment Tensors ◽  
Velocity Models ◽  
Double Couple ◽  
The Moment

SUMMARY Earthquake focal mechanisms put primary control on the distribution of ground motion, and also bear on the stress state of the crust. Most routine focal mechanism catalogues still use 1-D velocity models in inversions, which may introduce large uncertainties in regions with strong lateral velocity heterogeneities. In this study, we develop an automated waveform-based inversion approach to determine the moment tensors of small-to-medium-sized earthquakes using 3-D velocity models. We apply our approach in the Los Angeles region to produce a new moment tensor catalogue with a completeness of ML ≥ 3.5. The inversions using the Southern California Earthquake Center Community Velocity Model (3D CVM-S4.26) significantly reduces the moment tensor uncertainties, mainly owing to the accuracy of the 3-D velocity model in predicting both the phases and the amplitudes of the observed seismograms. By comparing the full moment tensor solutions obtained using 1-D and 3-D velocity models, we show that the percentages of non-double-couple components decrease dramatically with the usage of 3-D velocity model, suggesting that large fractions of non-double-couple components from 1-D inversions are artifacts caused by unmodelled 3-D velocity structures. The new catalogue also features more accurate focal depths and moment magnitudes. Our highly accurate, efficient and automatic inversion approach can be expanded in other regions, and can be easily implemented in near real-time system.

Velocity-estimation improvements and migration/demigration using the common-reflection surface with continuing deconvolution in the time domain

Geophysics ◽  
2019 ◽  
Vol 84 (4) ◽  
pp. S229-S238 ◽  
Author(s):  
Martina Glöckner ◽  
Sergius Dell ◽  
Benjamin Schwarz ◽  
Claudia Vanelle ◽  
Dirk Gajewski
Keyword(s):  
Model Building ◽  
Velocity Model ◽  
Velocity Estimation ◽  
Initial Time ◽  
Model Errors ◽  
Imaging Methods ◽  
Time Migration ◽  
Common Reflection Surface ◽  
The Common ◽  
And Migration

To obtain an image of the earth’s subsurface, time-imaging methods can be applied because they are reasonably fast, are less sensitive to velocity model errors than depth-imaging methods, and are usually easy to parallelize. A powerful tool for time imaging consists of a series of prestack time migrations and demigrations. We have applied multiparameter stacking techniques to obtain an initial time-migration velocity model. The velocity model building proposed here is based on the kinematic wavefield attributes of the common-reflection surface (CRS) method. A subsequent refinement of the velocities uses a coherence filter that is based on a predetermined threshold, followed by an interpolation and smoothing. Then, we perform a migration deconvolution to obtain the final time-migrated image. The migration deconvolution consists of one iteration of least-squares migration with an estimated Hessian. We estimate the Hessian by nonstationary matching filters, i.e., in a data-driven fashion. The model building uses the framework of the CRS, and the migration deconvolution is fully automated. Therefore, minimal user interaction is required to carry out the velocity model refinement and the image update. We apply the velocity refinement and migration deconvolution approaches to complex synthetic and field data.

Stacking apertures and estimation strategies for reflection and diffraction enhancement

Geophysics ◽  
2016 ◽  
Vol 81 (4) ◽  
pp. V271-V282 ◽  
Author(s):  
Jorge H. Faccipieri ◽  
Tiago A. Coimbra ◽  
Leiv-J. Gelius ◽  
Martin Tygel
Keyword(s):  
Fresnel Zone ◽  
Careful Selection ◽  
Time Migration ◽  
Key Factor ◽  
Common Reflection Surface ◽  
Good Potential ◽  
Image Quality Improvement ◽  
The Common ◽  
Selection Of

It is well known that the quality of stacking results (e.g., noise reduction, event enhancement, and continuity) can be greatly influenced not only by the traveltime operator chosen but also by the apertures used. We have considered two so-called diffraction-stack traveltimes, together with the corresponding apertures, designed to enhance reflections and diffractions, respectively. The first one is the common-reflection-surface (CRS) diffraction traveltime that is obtained from the general CRS traveltime upon the condition that the target reflector reduced to a point, which we refer to as the diffraction CRS (DCRS) traveltime. The second one is the double-square-root (DSR) traveltime, well established in time migration. We have observed that the DCRS and DSR traveltimes depend on fewer parameters (two in 2D and five in 3D) than the full CRS traveltime (three in 2D and eight in 3D). For the DCRS and DSR traveltimes, we have proposed specific apertures based on the projected Fresnel zone, which are able to produce high-quality stacked sections using less parameters to be estimated. The key factor in that approach lies in the choice of traveltime operators together with careful selection of stacking apertures. In particular, suitable choices of operators and apertures lead to stacking volumes in which reflections are enhanced (and the diffractions are attenuated) or the corresponding ones in which diffractions are enhanced (and reflections are attenuated). Synthetic and field data confirm the proposed approach has good potential for image-quality improvement.

Elastic reflection waveform inversion based on the decomposition of sensitivity kernels

Geophysics ◽  
2019 ◽  
Vol 84 (2) ◽  
pp. R235-R250 ◽  
Author(s):  
Zhiming Ren ◽  
Zhenchun Li ◽  
Bingluo Gu
Keyword(s):  
Wave Velocity ◽  
Waveform Inversion ◽  
Velocity Model ◽  
P Wave ◽  
Background Model ◽  
Reverse Time ◽  
S Wave ◽  
Velocity Models ◽  
Time Migration ◽  
Starting Model

Full-waveform inversion (FWI) has the potential to obtain an accurate velocity model. Nevertheless, it depends strongly on the low-frequency data and the initial model. When the starting model is far from the real model, FWI tends to converge to a local minimum. Based on a scale separation of the model (into the background model and reflectivity model), reflection waveform inversion (RWI) can separate out the tomography term in the conventional FWI kernel and invert for the long-wavelength components of the velocity model by smearing the reflected wave residuals along the transmission (or “rabbit-ear”) paths. We have developed a new elastic RWI method to build the P- and S-wave velocity macromodels. Our method exploits a traveltime-based misfit function to highlight the contribution of tomography terms in the sensitivity kernels and a sensitivity kernel decomposition scheme based on the P- and S-wave separation to suppress the high-wavenumber artifacts caused by the crosstalk of different wave modes. Numerical examples reveal that the gradients of the background models become sufficiently smooth owing to the decomposition of sensitivity kernels and the traveltime-based misfit function. We implement our elastic RWI in an alternating way. At each loop, the reflectivity model is generated by elastic least-squares reverse time migration, and then the background model is updated using the separated traveltime kernels. Our RWI method has been successfully applied in synthetic and real reflection seismic data. Inversion results demonstrate that the proposed method can retrieve preferable low-wavenumber components of the P- and S-wave velocity models, which are reliable to serve as a starting model for conventional elastic FWI. Also, our method with a two-stage inversion workflow, first updating the P-wave velocity using the PP kernels and then updating the S-wave velocity using the PS kernels, is feasible and robust even when P- and S-wave velocities have different structures.

Improving seismic image using the common-horizon panel

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. S449-S458
Author(s):  
Lu Liu
Keyword(s):  
Time Lag ◽  
Velocity Model ◽  
Migration Velocity ◽  
Quantitative Information ◽  
Time Shift ◽  
Velocity Models ◽  
Seismic Image ◽  
The Common ◽  
Seismic Images ◽  
Zero Time

Generating high-quality seismic images requires accurate velocity models. However, velocity errors are predictably brought into the models. To mitigate the influences of velocity errors, we have used the common-horizon panel (CHP) for migration velocity analysis. CHP provides quantitative information to adjust mispositioned interfaces or correct deformed wavefields, which leads to improved image quality. It is generated by extrapolating seismic gathers to a selected target horizon and applying the time-shift imaging condition. Compared with the commonly used common-image gathers, the events in CHPs are more trackable because geologic interfaces are typically continuous in space. For a correct velocity model, the panel indicates a flat event at zero time lag, whereas in the case of an erroneous velocity model, the event becomes kinematically oscillating. This distinguishing difference provides a practical criterion to verify whether the migration velocity model is correct and to estimate the velocity or wavefield errors based on how much the event deviates from zero time lag. Tests on synthetic and field data sets have shown that the seismic images are improved by using the proposed CHP technique.

Overburden dependent AVA inversion

Geophysics ◽  
2010 ◽  
Vol 75 (2) ◽  
pp. C15-C23 ◽  
Author(s):  
Lyubov Skopintseva ◽  
Alexey Stovas
Keyword(s):  
Error Estimates ◽  
Velocity Model ◽  
Model Parameters ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Avo Analysis ◽  
Velocity Models ◽  
Model Interpretation

Amplitude-variation-with-offset (AVO) analysis is strongly dependent on interpretation of the estimated traveltime parameters. In practice, we can estimate two or three traveltime parameters that require interpretation within the families of two- or three-parameter velocity models, respectively. Increasing the number of model parameters improves the quality of overburden description and reduces errors in AVO analysis. We have analyzed the effect of two- and three-parameter velocity model interpretation for the overburden on AVO data and have developed error estimates in the reservoir parameters.

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