Residual depth moveout and velocity determination for parametric media

Geophysics ◽  
2008 ◽  
Vol 73 (5) ◽  
pp. VE361-VE367 ◽  
Author(s):  
Joerg Schneider
Keyword(s):  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Suggested Approach ◽  
Depth Migration ◽  
Velocity Models ◽  
Variation Of Parameters ◽  
Wide Range ◽  
Large Velocity ◽  
Zero Offset ◽  
Made In

For the case when prestack depth migration has been performed with inaccurate velocities, it can be shown that second-order approximations can be used to predict the residual depth moveout of common-image and angle-domain common-image gathers. Corrections may be made in terms of offset and common-reflection angles that can be estimated from the migrated data using moveout analysis schemes. The residual moveout determined can be used to improve the signal-to-noise ratio of the migrated data and to determine the variation of parameters of well-known formation-dependent velocity laws away from borehole positions. Although the method is developed for small offsets, reflection angles, and velocity differences, realistic examples may be used to demonstrate that satisfactory approximations to the residual moveout curve can be obtained over a relatively wide range of offsets or reflection angles and for moderate velocity differences. A zero-offset inversion was applied to the estimated residual radii of curvature. This inversion was performed layerwise. For each layer, the velocity was assumed to vary according to a known depth-varying and a laterally varying component to be determined. Iterative applications of the suggested approach have rendered satisfactory results for several representative velocity models. For each application, appropriate initial models were provided. Applications to initial models with large velocity differences and to seismic data with large offsets have to be investigated.

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.

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.

Imaging passive seismic data

Geophysics ◽  
2006 ◽  
Vol 71 (4) ◽  
pp. SI177-SI187 ◽  
Author(s):  
Brad Artman
Keyword(s):  
Water Table ◽  
Seismic Data ◽  
Survey Design ◽  
Signal To Noise Ratio ◽  
Multiple Sources ◽  
Depth Migration ◽  
Reflection Seismic ◽  
Ambient Sound ◽  
Passive Seismic ◽  
Passive Data

Imaging passive seismic data is the process of synthesizing the wealth of subsurface information available from reflection seismic experiments by recording ambient sound using an array of geophones distributed at the surface. Crosscorrelating the traces of such a passive experiment can synthesize data that are identical to actively collected reflection seismic data. With a correlation-based imaging condition, wave-equation shot-profile depth migration can use raw transmission wavefields as input for producing a subsurface image. Migration is even more important for passively acquired data than for active data because with passive data, the source wavefields are likely to be weak compared with background and instrument noise — a condition that leads to a low signal-to-noise ratio. Fourier analysis of correlating long field records shows that aliasing of the wavefields from distinct shots is unavoidable. Although this reduces the order of computations for correlation by the length of the original trace, the aliasing produces an output volume that may not be substantially more useful than the raw data because of the introduction of crosstalk between multiple sources. Direct migration of raw field data still can produce an accurate image, even when the transmission wavefields from individual sources are not separated. To illustrate direct migration, I use images from a shallow passive seismic investigation targeting a buried hollow pipe and the water-table reflection. These images show a strong anomaly at the 1-m depth of the pipe and faint events that could be the water table at a depth of around [Formula: see text]. The images are not clear enough to be irrefutable. I identify deficiencies in survey design and execution to aid future efforts.

Diffraction imaging and depth-velocity inversion with 3D P-Cable seismic data

2021 ◽  
Author(s):  
Alexander Bauer ◽  
Benjamin Schwarz ◽  
Dirk Gajewski
Keyword(s):  
Seismic Data ◽  
Model Building ◽  
Computational Cost ◽  
Velocity Model ◽  
Data Cube ◽  
Velocity Inversion ◽  
Velocity Models ◽  
North East ◽  
3D Velocity Model ◽  
Zero Offset

<p>Most established methods for the estimation of subsurface velocity models rely on the measurements of reflected or diving waves and therefore require data with sufficiently large source-receiver offsets. For seismic data that lacks these offsets, such as vintage data, low-fold academic data or near zero-offset P-Cable data, these methods fail. Building on recent studies, we apply a workflow that exploits the diffracted wavefield for depth-velocity-model building. This workflow consists of three principal steps: (1) revealing the diffracted wavefield by modeling and adaptively subtracting reflections from the raw data, (2) characterizing the diffractions with physically meaningful wavefront attributes, (3) estimating depth-velocity models with wavefront tomography. We propose a hybrid 2D/3D approach, in which we apply the well-established and automated 2D workflow to numerous inlines of a high-resolution 3D P-Cable dataset acquired near Ritter Island, a small volcanic island located north-east of New Guinea known for a catastrophic flank collapse in 1888. We use the obtained set of parallel 2D velocity models to interpolate a 3D velocity model for the whole data cube, thus overcoming possible issues such as varying data quality in inline and crossline direction and the high computational cost of 3D data analysis. Even though the 2D workflow may suffer from out-of-plane effects, we obtain a smooth 3D velocity model that is consistent with the data.</p>

Unified imaging of multichannel seismic data: Combining traveltime inversion and prestack depth migration

Geophysics ◽  
2008 ◽  
Vol 73 (5) ◽  
pp. VE269-VE280 ◽  
Author(s):  
Priyank Jaiswal ◽  
Colin A. Zelt
Keyword(s):  
Seismic Data ◽  
Joint Inversion ◽  
Velocity Model ◽  
Depth Image ◽  
Prestack Depth Migration ◽  
Traveltime Inversion ◽  
Depth Migration ◽  
Interval Velocity ◽  
Wide Aperture ◽  
Zero Offset

Imaging 2D multichannel land seismic data can be accomplished effectively by a combination of traveltime inversion and prestack depth migration (PSDM), referred to as unified imaging. Unified imaging begins by inverting the direct-arrival times to estimate a velocity model that is used in static corrections and stacking velocity analysis. The interval velocity model (from stacking velocities) is used for PSDM. The stacked data and the PSDM image are interpreted for common horizons, and the corresponding wide-aperture reflections are identified in the shot gathers. Using the interval velocity model, the stack interpretations are inverted as zero-offset reflections to constrain the corresponding interfaces in depth; the interval velocity model remains stationary. We define a coefficient of congruence [Formula: see text] that measures the discrepancy between horizons from the PSDM image andtheir counterparts from the zero-offset inversion. A value of unity for [Formula: see text] implies that the interpreted and inverted horizons are consistent to within the interpretational uncertainties, and the unified imaging is said to have converged. For [Formula: see text] greater than unity, the interval velocity model and the horizon depths are updated by jointly inverting the direct arrivals with the zero-offset and wide-aperture reflections. The updated interval velocity model is used again for both PSDM and a zero-offset inversion. Interpretations of the new PSDM image are the updated horizon depths. The unified imaging is applied to seismic data from the Naga Thrust and Fold Belt in India. Wide-aperture and zero-offset data from three geologically significant horizons are used. Three runs of joint inversion and PSDM are required in a cyclic manner for [Formula: see text] to converge to unity. A joint interpretation of the final velocity model and depth image reveals the presence of a triangle zone that could be promising for exploration.

Application of diffraction wavefront tomography to GPR data from a glacier

2020 ◽  
Author(s):  
Alexander Bauer ◽  
Benjamin Schwarz ◽  
Richard Delf ◽  
Dirk Gajewski
Keyword(s):  
Seismic Data ◽  
Velocity Model ◽  
High Amplitude ◽  
Small Scale ◽  
Coherence Analysis ◽  
Raw Data ◽  
Seismic Reflection Data ◽  
Velocity Models ◽  
Passive Seismic ◽  
Zero Offset

<p>In the recent years, the diffracted wavefield has gained increasing attention in the field of applied seismics. While classical seismic imaging and inversion schemes mainly focus on high-amplitude reflected measurements, the faint and often masked diffracted wavefield is neglected or even treated as noise. In order to be able to extract depth-velocity models from seismic reflection data, sufficiently large source-receiver offsets are needed. However, the acquisition of such multi-channel seismic data is expensive and often only feasible for the hydrocarbon industry, while academia has to cope with low-fold or zero-offset data. The diffracted wavefield is the key for extracting depth velocities from such data, as the moveout of diffractions – in contrast to reflections – can be measured in the zero-offset domain. Recently, we have demonstrated on multi-channel, single-channel and passive seismic data that by means of wavefront tomography depth-velocity models can be retrieved solely based on diffractions or passive seismic events along with the localizations of these scatterers. The input for wavefront tomography are so-called wavefront attributes, which can be extracted from the data in an unsupervised fashion by means of coherence analysis. In order to obtain the required diffraction-only data, we use a recently proposed scheme that adaptively subtracts the high-amplitude reflected wavefield from the raw data. Due to their most common acquisition geometry, most ground-penetrating-radar (GPR) data inherently lack offsets. In addition, GPR data generally contain a rich diffracted wavefield, which in turn contains information about sought-after structures, as diffractions are caused by small-scale heterogeneities such as faults, tips or edges. In this work, we show an application of the suggested workflow – coherence analysis, diffraction separation and diffraction wavefront tomography – to GPR data acquired at a glacier, resulting in a depth-velocity model and the localizations of the scatterers, both obtained in a fully unsupervised fashion. While the resulting  velocity model may be used for depth migration of the raw data, the localizations of the scatterers may in addition provide important information on the inner structure of the glacier in order to, for instance, localize water intrusions or fractures.</p>

Three‐dimensional depth imaging with generalized screens: A salt body case study

Geophysics ◽  
2003 ◽  
Vol 68 (4) ◽  
pp. 1132-1139 ◽  
Author(s):  
Jérôme H. Le Rousseau ◽  
Henry Calandra ◽  
Maarten V. de Hoop
Keyword(s):  
Three Dimensional ◽  
Fourier Method ◽  
Seismic Survey ◽  
Tectonic Deformation ◽  
Data Set ◽  
Depth Imaging ◽  
Depth Migration ◽  
Velocity Models ◽  
The North ◽  
Zero Offset

We illustrate the performance of the generalized screen propagator on real seismic data for 3D zero‐offset and prestack depth imaging. We use TotalFinaElf's L7D data set from the North Sea, a 3D marine seismic survey that contained limited azimuthal coverage. The subsurface shows significant tectonic deformation, including an intrusive salt body in sedimentary sequences. A transformation to common azimuth is applied prior to the 3D prestack depth imaging procedure. We compare the performance of the generalized screen propagator with that of a hybrid phase shift plus interpolation (PSPI)/split‐step Fourier method. Three‐dimensional prestack results confirm the generalized screen method handles multipathing more accurately. Comparisons are also made with Kirchhoff migration results. The results differ mainly in the fine‐scale irregularities of the image and not in the wavefront set of the image. Using synthetic models of similar structure (the SEG/EAGE salt model), we further illustrate the importance of multipathing and multiple scattering. Overall, our results show that our wave‐equation approach produces better images than the Kirchhoff approach to prestack depth migration; we attribute this mainly to a more complete handling of wave diffraction in the generalized screen expansion, which becomes important in strongly heterogeneous and irregular velocity models such as the ones containing salt bodies.

Seismic imaging using lateral adaptive windows

Geophysics ◽  
2010 ◽  
Vol 75 (2) ◽  
pp. S73-S79
Author(s):  
Ørjan Pedersen ◽  
Sverre Brandsberg-Dahl ◽  
Bjørn Ursin
Keyword(s):  
Seismic Data ◽  
Seismic Imaging ◽  
Synthetic Data ◽  
Real Data ◽  
Extrapolation Methods ◽  
Depth Migration ◽  
Large Velocity ◽  
Migration Method ◽  
Wavefield Extrapolation ◽  
The Impact

One-way wavefield extrapolation methods are used routinely in 3D depth migration algorithms for seismic data. Due to their efficient computer implementations, such one-way methods have become increasingly popular and a wide variety of methods have been introduced. In salt provinces, the migration algorithms must be able to handle large velocity contrasts because the velocities in salt are generally much higher than in the surrounding sediments. This can be a challenge for one-way wavefield extrapolation methods. We present a depth migration method using one-way propagators within lateral windows for handling the large velocity contrasts associated with salt-sediment interfaces. Using adaptive windowing, we can handle large perturbations locally in a similar manner as the beamlet propagator, thus limiting the impact of the errors on the global wavefield. We demonstrate the performance of our method by applying it to synthetic data from the 2D SEG/EAGE [Formula: see text] salt model and an offshore real data example.

Sign in / Sign up

Export Citation Format

Share Document