Application of the migration velocity analysis to a long-offset seismic data in the Ulleung basin, offshore Korea

2020 ◽  
Author(s):  
Woohyun Son ◽  
Byoung-Yeop Kim
Keyword(s):  
Seismic Data ◽  
Velocity Structure ◽  
Velocity Model ◽  
Ulleung Basin ◽  
Velocity Analysis ◽  
Time Processing ◽  
Depth Processing ◽  
Migration Velocity Analysis ◽  
Long Offset ◽  
Marine Seismic

<p>In order to obtain subsurface velocity for field seismic data, a time processing based on semblance velocity analysis has been performed so far. However, since the results of the time processing do not provide velocity information in the depth domain, it is difficult to know the exact subsurface velocity. In this study, to generate accurate velocity, the depth processing using the migration velocity analysis (MVA), which generates more reasonable subsurface velocity structure than the result from the time processing, is applied to the field marine seismic data obtained from Ulleung basin (offshore Korea). A marine seismic source is generated by air-gun (2,289 cu. in.). The long-offset (5.7 km) multichannel seismic (MCS) data were recorded by 456 receivers. The source and receiver spacings are 25 m and 12.5 m, respectively. The seismic survey line is about 168 L-km. The MVA workflow is composed of building a starting velocity model, sorting data to common offset gathers, Kirchhoff prestack depth migration (PSDM), sorting to common reflection point (CRP) gathers, picking residual moveout (RMO), and updating the velocity model. We repeatedly applied the MVA workflow until the remarkable events in the CRP gather were flat. From the results, we could confirm that the depth processing using MVA is successfully applied to field dataset and generates reasonable velocity structure in depth.</p>

scholarly journals Pre-stack 3-D Tau migration and velocity analysis: application to 3-D seismic data from offshore Abu Dhabi, United Arab Emirates

GeoArabia ◽  
2006 ◽  
Vol 11 (3) ◽  
pp. 43-60
Author(s):  
Tariq Alkhalifah ◽  
Saif Al Sharif ◽  
Kamal Belaid
Keyword(s):  
United Arab Emirates ◽  
Seismic Data ◽  
Velocity Model ◽  
Migration Velocity ◽  
Abu Dhabi ◽  
Velocity Analysis ◽  
Low Velocity ◽  
Data Set ◽  
Velocity Anomaly ◽  
Migration Velocity Analysis

ABSTRACT A pre-stack 3-D Tau migration was applied to a 3-D seismic data set acquired in offshore Abu Dhabi, United Arab Emirates. The velocity model was built through an initial series of 2-D Tau migration velocity analysis, and supplemented by 3-D subset migration. A 3-D Tau migration velocity analysis was used for the final two updates of the model. The final interval velocity model provided low residuals in the common-image gathers from different offsets and was consistent with velocities from four wells located in the region. This velocity model included the main known features of the region including a low-velocity zone and a major fault. A final 3-D pre-stack Tau migration was applied using the velocity model and a relatively moderate aperture. This migration imaged the region including part of the critical poor data quality region, which includes the reservoir as well as reflections from the fault. Based on the derived velocity model, we concluded that the major cause for the poor image is the presence of a shallow high-velocity anomaly separated by a fault from a low-velocity anomaly.

Migration velocity analysis from locally coherent events in 2‐D laterally heterogeneous media, Part I: Theoretical aspects

Geophysics ◽  
2002 ◽  
Vol 67 (4) ◽  
pp. 1202-1212 ◽  
Author(s):  
Hervé Chauris ◽  
Mark S. Noble ◽  
Gilles Lambaré ◽  
Pascal Podvin
Keyword(s):  
Cost Function ◽  
Velocity Model ◽  
Migration Velocity ◽  
Velocity Estimation ◽  
Velocity Analysis ◽  
Seismic Reflection Data ◽  
Velocity Models ◽  
Migration Velocity Analysis ◽  
Paraxial Ray ◽  
The Cost

We present a new method based on migration velocity analysis (MVA) to estimate 2‐D velocity models from seismic reflection data with no assumption on reflector geometry or the background velocity field. Classical approaches using picking on common image gathers (CIGs) must consider continuous events over the whole panel. This interpretive step may be difficult—particularly for applications on real data sets. We propose to overcome the limiting factor by considering locally coherent events. A locally coherent event can be defined whenever the imaged reflectivity locally shows lateral coherency at some location in the image cube. In the prestack depth‐migrated volume obtained for an a priori velocity model, locally coherent events are picked automatically, without interpretation, and are characterized by their positions and slopes (tangent to the event). Even a single locally coherent event has information on the unknown velocity model, carried by the value of the slope measured in the CIG. The velocity is estimated by minimizing these slopes. We first introduce the cost function and explain its physical meaning. The theoretical developments lead to two equivalent expressions of the cost function: one formulated in the depth‐migrated domain on locally coherent events in CIGs and the other in the time domain. We thus establish direct links between different methods devoted to velocity estimation: migration velocity analysis using locally coherent events and slope tomography. We finally explain how to compute the gradient of the cost function using paraxial ray tracing to update the velocity model. Our method provides smooth, inverted velocity models consistent with Kirchhoff‐type migration schemes and requires neither the introduction of interfaces nor the interpretation of continuous events. As for most automatic velocity analysis methods, careful preprocessing must be applied to remove coherent noise such as multiples.

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.

2-D continuation operators and their applications

Geophysics ◽  
1996 ◽  
Vol 61 (6) ◽  
pp. 1846-1858 ◽  
Author(s):  
Claudio Bagaini ◽  
Umberto Spagnolini
Keyword(s):  
Seismic Data ◽  
Real Data ◽  
Integral Form ◽  
Amplitude Distribution ◽  
Velocity Model ◽  
Velocity Analysis ◽  
Seismic Data Processing ◽  
Analysis Method ◽  
Standard Tool ◽  
Zero Offset

Continuation to zero offset [better known as dip moveout (DMO)] is a standard tool for seismic data processing. In this paper, the concept of DMO is extended by introducing a set of operators: the continuation operators. These operators, which are implemented in integral form with a defined amplitude distribution, perform the mapping between common shot or common offset gathers for a given velocity model. The application of the shot continuation operator for dip‐independent velocity analysis allows a direct implementation in the acquisition domain by exploiting the comparison between real data and data continued in the shot domain. Shot and offset continuation allow the restoration of missing shot or missing offset by using a velocity model provided by common shot velocity analysis or another dip‐independent velocity analysis method.

Iterative P-wave velocity inversion using Markov chain Monte Carlo method

2020 ◽  
Author(s):  
Hyunggu Jun ◽  
Hyeong-Tae Jou ◽  
Han-Joon Kim ◽  
Sang Hoon Lee
Keyword(s):  
Wave Velocity ◽  
Seismic Data ◽  
Velocity Structure ◽  
Low Frequency ◽  
P Wave ◽  
Velocity Analysis ◽  
Seismic Section ◽  
Traveltime Tomography ◽  
P Wave Velocity ◽  
Frequency Components

<p>Imaging the subsurface structure through seismic data needs various information and one of the most important information is the subsurface P-wave velocity. The P-wave velocity structure mainly influences on the location of the reflectors during the subsurface imaging, thus many algorithms has been developed to invert the accurate P-wave velocity such as conventional velocity analysis, traveltime tomography, migration velocity analysis (MVA) and full waveform inversion (FWI). Among those methods, conventional velocity analysis and MVA can be widely applied to the seismic data but generate the velocity with low resolution. On the other hands, the traveltime tomography and FWI can invert relatively accurate velocity structure, but they essentially need long offset seismic data containing sufficiently low frequency components. Recently, the stochastic method such as Markov chain Monte Carlo (McMC) inversion was applied to invert the accurate P-wave velocity with the seismic data without long offset or low frequency components. This method uses global optimization instead of local optimization and poststack seismic data instead of prestack seismic data. Therefore, it can avoid the problem of the local minima and limitation of the offset. However, the accuracy of the poststack seismic section directly affects the McMC inversion result. In this study, we tried to overcome the dependency of the McMC inversion on the poststack seismic section and iterative workflow was applied to the McMC inversion to invert the accurate P-wave velocity from the simple background velocity and inaccurate poststack seismic section. The numerical test showed that the suggested method could successfully invert the subsurface P-wave velocity.</p>

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