Reducing 3-D acquisition footprint for 3-D DMO and 3-D prestack migration

Geophysics ◽  
1998 ◽  
Vol 63 (4) ◽  
pp. 1177-1183 ◽  
Author(s):  
Anat Canning ◽  
Gerald H. F. Gardner
Keyword(s):  
Spatial Distribution ◽  
Velocity Analysis ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Prestack Migration ◽  
Avo Analysis ◽  
And Migration

The acquisition patterns of 3-D surveys often have a significant effect on the results of dip moveout (DMO) or prestack migration. When the spatial distribution of input traces is irregular, results from DMO and migration are contaminated by artifacts. In many cases, the footprint of the acquisition patterns can be seen on the migrated section and may result in incorrect interpretation. This phenomena also has a very significant effect on the feasibility of conducting amplitude variation with offset (AVO) analysis after 3-D prestack migration or after 3-D DMO, and also may affect velocity analysis. We propose a simple enhancement to migration and DMO programs that acts to minimize acquisition artifacts.

A method to compensate for migration stretch to improve the resolution of amplitude variation with offset, S-impedance (ZS), and density (ρ)

2020 ◽  
Vol 8 (4) ◽  
pp. T687-T699
Author(s):  
Swetal Patel ◽  
Francis Oyebanji ◽  
Kurt J. Marfurt
Keyword(s):  
Matching Pursuit ◽  
Azimuthal Anisotropy ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Prestack Migration ◽  
Fort Worth Basin ◽  
Seismic Wavelet ◽  
Compensation Factor ◽  
Nmo Correction ◽  
And Migration

Because of their improved leverage against ground roll and multiples, as well as the ability to estimate azimuthal anisotropy, wide-azimuth 3D seismic surveys routinely now are acquired over most resource plays. For a relatively shallow target, most of these surveys can be considered to be long offset as well, containing incident angles up to 45°. Unfortunately, effective use of the far-offset data often is compromised by noise and normal moveout (NMO) (or, more accurately, prestack migration) stretch. The conventional NMO correction is well-known to decrease the frequency content and distort the seismic wavelet at far offsets, sometimes giving rise to tuning effects. Most quantitative interpreters work with prestack migrated gathers rather than unmigrated NMO-corrected gathers. However, prestack migration of flat reflectors suffers from the same limitation called migration stretch. Migration stretch leads to lower S-impedance ([Formula: see text]) and density ([Formula: see text]) resolution estimated from inversion, misclassification of amplitude variation with offset (AVO) types, and infidelity in amplitude variation with azimuth (AVAZ) inversion results. We have developed a matching pursuit algorithm commonly used in spectral decomposition to correct the migration stretch by scaling the stretched wavelets using a wavelet compensation factor. The method is based on hyperbolic moveout approximation. The corrected gathers show increased resolution and higher fidelity amplitudes at the far offsets leading to improvement in AVO classification. Correction for migration stretch rather than conventional “stretch-mute” corrections provides three advantages: (1) preservation of far angles required for accurate [Formula: see text] inversion, (2) improvement in the vertical resolution of [Formula: see text] and [Formula: see text] volumes, and (3) preservation of far angles that provide greater leverage against multiples. We apply our workflow to data acquired in the Fort Worth Basin and retain incident angles up to 42° at the Barnett Shale target. Comparing [Formula: see text], [Formula: see text], and [Formula: see text] of the original gather and migration stretch-compensated data, we find an insignificant improvement in [Formula: see text], but a moderate to significant improvement in resolution of [Formula: see text] and [Formula: see text]. The method is valid for reservoirs that exhibit a dip of no more than 2°. Consistent improvement is observed in resolving thick beds, but the method might introduce amplitude anomalies at far offsets for tuning beds.

scholarly journals AVO analysis for high amplitude anomalies using 2D pre-stack seismic data

2022 ◽  
Author(s):  
Lamees N. Abdulkareem ◽  
Keyword(s):  
Seismic Data ◽  
High Amplitude ◽  
Rock Properties ◽  
Fluid Substitution ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
The Real ◽  
North West ◽  
Avo Analysis ◽  
Controlling Parameter

Amplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the controlling parameter on the AVO analysis. AVO cross plots from the real pre-stack seismic data reveal AVO class IV (showing a negative intercept decreasing with offset). This result matches our modelled result of fluid substitution for the seismic synthetics. It is concluded that fluid substitution is the controlling parameter on the AVO analysis and therefore, the high amplitude anomaly on the seabed and the target horizon 9 is the result of changing the fluid content and the lithology along the target horizons. While changing the porosity has little effect on the amplitude variation with offset within the AVO cross plot. Finally, results from the wedge models show that a small change of thickness causes a change in the amplitude; however, this change in thickness gives a different AVO characteristic and a mismatch with the AVO result of the real 2D pre-stack seismic data. Therefore, a constant thin layer with changing fluids is more likely to be the cause of the high amplitude anomalies.

The vertical image projection method for migration stretch compensation

2021 ◽  
pp. 1-55
Author(s):  
Arash JafarGandomi
Keyword(s):  
Real Data ◽  
Amplitude Variation ◽  
Seismic Migration ◽  
Amplitude Variation With Offset ◽  
Amplitude Inversion ◽  
Image Projection ◽  
And Migration ◽  
Avo Attributes ◽  
Conditioning Approach ◽  
The Impact

True amplitude inversion is often carried out without taking into account migration distortions to the wavelet. Seismic migration leaves a dip-dependent effect on the wavelet that can cause significant inaccuracies in the inverted impedances obtained from conventional inversion approaches based on 1D vertical convolutional modelling. Neglecting this effect causes misleading inversion results and leakage of dipping noise and migration artifacts from higher frequency bands to the lower frequencies. I have observed that despite dip-dependency of this effect, low-dip and flat events may also suffer if they are contaminated with cross-cutting noise, steep migration artifacts, and smiles. In this paper I propose an efficient, effective and reversible data pre-conditioning approach that accounts for dip-dependency of the wavelet and is applied to migrated images prior to inversion. My proposed method consists of integrating data with respect to the total wavenumber followed by the differentiation with respect to the vertical wavenumber. This process is equivalent to applying a deterministic dip-consistent pre-conditioning that projects the data from the total wavenumber to the vertical wavenumber axis. This preconditioning can be applied to both pre- and post-stack data as well as to amplitude variation with offset (AVO) attributes such as intercept and gradient before inversion. The vertical image projection methodology that I propose here reduces the impact of migration artifacts such as cross-cutting noise and migration smiles and improves inverted impedances in both synthetic and real data examples. In particular I show that neglecting the proposed pre-conditioning leads to anomalously higher impedance values along the steeply dipping structures.

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.

scholarly journals Fracture clustering effect on amplitude variation with offset and azimuth analyses

Geophysics ◽  
2017 ◽  
Vol 82 (1) ◽  
pp. N13-N25 ◽  
Author(s):  
Xinding Fang ◽  
Yingcai Zheng ◽  
Michael C. Fehler
Keyword(s):  
Effective Medium Theory ◽  
Effective Medium ◽  
Amplitude Variation ◽  
Medium Theory ◽  
Fracture Characterization ◽  
Amplitude Variation With Offset ◽  
Fracture Properties ◽  
Fracture Spacing ◽  
Avo Analysis ◽  
Irregular Spacing

Traditional amplitude variation with offset and azimuth (AVOAz) analysis for fracture characterization extracts fracture properties through analysis of reflection AVOAz to determine anisotropic parameters (e.g., Thomsen’s parameters) that are then related to fracture properties. The validity of this method relies on the basic assumption that a fractured unit can be viewed as an equivalent anisotropic medium. As a rule of thumb, this assumption is taken to be valid when the fracture spacing is less than [Formula: see text]. Under the effective medium assumption, diffractions from individual fractures destructively interfere and only specular reflections from boundaries of a fractured layer can be observed in seismic data. The effective medium theory has been widely used in fracture characterization, and its applicability has been validated through many field applications. However, through numerical simulations, we find that diffractions from fracture clusters can significantly distort the AVOAz signatures when a fracture system has irregular spacing even though the average fracture spacing is much smaller than a wavelength (e.g., [Formula: see text]). Contamination by diffractions from irregularly spaced fractures on reflections can substantially bias the fracture properties estimated from AVOAz analysis and may possibly lead to incorrect estimates of fracture properties. Additionally, through Monte Carlo simulations, we find that fracture spacing uncertainty inverted from amplitude variation with offset (AVO) analysis can be up to 10%–20% when fractures are not uniformly distributed, which should be the realistic state of fractures present in the earth. Also, AVOAz and AVO analysis gives more reliable estimates of fracture properties when reflections at the top of the fractured layer are used compared with those from the bottom of the layer.

Amplitude variation with offset-friendly bootstrapped differential semblance

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. V297-V309 ◽  
Author(s):  
Hamish Wilson ◽  
Lutz Gross
Keyword(s):  
Spectral Resolution ◽  
Seismic Data ◽  
Velocity Analysis ◽  
Apparent Velocity ◽  
Seismic Data Processing ◽  
Velocity Control ◽  
Amplitude Variation ◽  
Trade Off ◽  
Amplitude Variation With Offset ◽  
Velocity Models

Spectral noise, low resolution, and attenuation of semblance peaks due to amplitude variation with offset (AVO) anomalies hamper the reliability of velocity analysis in the semblance spectrum for seismic data processing. Increasing resolution and reducing noise while accounting for AVO has posed a challenge in various semblance schemes due to a trade-off in resolution and AVO detectability. A new semblance scheme is introduced that aims to remove this trade-off. The new scheme uses the concepts of bootstrapped differential semblance with trend-based AB semblance. Results indicate that the new scheme indeed increases spectral resolution, reduces noise, and accounts for AVO anomalies. These improvements facilitate velocity control for automatic and manual picking methods and, hence, provide a means for more reliable apparent velocity models.

Velocity analysis in the presence of amplitude variation

Geophysics ◽  
2002 ◽  
Vol 67 (5) ◽  
pp. 1664-1672 ◽  
Author(s):  
Debashish Sarkar ◽  
Robert T. Baumel ◽  
Ken L. Larner
Keyword(s):  
Seismic Data ◽  
Degrees Of Freedom ◽  
Velocity Analysis ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Numerical Tests ◽  
Class 1 ◽  
Signal Peak ◽  
Polarity Reversals

Conventional semblance velocity analysis is equivalent to modeling prestack seismic data with events that have hyperbolic moveout but no amplitude variation with offset (AVO). As a result of its assumption that amplitude is independent of offset, this method might be expected to perform poorly for events with strong AVO—especially for events with polarity reversals at large offset, such as reflections from tops of some class 1 and class 2 sands. We find that substantial amplitude variation and even phase change with offset do not compromise the conventional semblance measure greatly. Polarity reversal, however, causes conventional semblance to fail. The semblance method can be extended to take into account data with events that have amplitude variation, expressed by AVO intercept and gradient (i.e., the Shuey approximation). However, because of the extra degrees of freedom introduced in AVO‐sensitive semblance, resolution of the estimated velocities is decreased. This is because the data can be modeled acceptably with a range of combined erroneous velocity and AVO behavior. To address this problem, in addition to using the Shuey equation to describe the amplitude variation, we constrain the AVO parameters (intercept and gradient) to be related linearly within each semblance window. With this constraint we can preserve velocity resolution and improve the quality of velocity analysis in the presence of amplitude and even polarity variation with offset. Results from numerical tests suggest that the modified semblance is accurate in the presence of polarity reversals. Tests also indicate, however, that in the presence of noise, the signal peak in conventional semblance has better standout than does that in the modified semblance measures.

Source wavelet and local wave propagation effects on the amplitude-variation-with-offset response of thin-layer models: A physical modeling study

Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. N27-N41 ◽  
Author(s):  
Carlos A. M. Assis ◽  
Sérgio A. M. Oliveira ◽  
Roseane M. Misságia ◽  
Marco A. R. de Ceia
Keyword(s):  
Wave Propagation ◽  
Thin Layer ◽  
Thin Layers ◽  
Propagation Mode ◽  
Multiple Reflections ◽  
Amplitude Response ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Avo Analysis ◽  
Reflection Data

In target layers with thicknesses below the vertical seismic resolution as thin layers, the tuning effect/interference between the wave propagation modes may increase the challenge of doing amplitude-variation-with-offset (AVO) analysis because it is difficult to recover the primary PP amplitudes embedded in the data by further seismic data processing. Thus, we have investigated the importance of the primary PP reflections, locally P-SV converted waves, and internal multiple reflections in the amplitude response of two thin-layer seismic physical models. One model consists of a thin water layer embedded between two nylon plates, and another model with a thin acrylic layer surrounded by water. Numerical modeling using the reflectivity method was applied to analyze each wave propagation mode and the source waveform role in the experimental data. Before the experimental reflection data acquisition, we characterized two source and receiver piezoelectric transducer (PET) pairs: one with a circular plane face and the other with a semispherical face. We measured the source wavelet, its dominant frequency, and the PETs’ directivity pattern. Semispherical PETs were chosen to acquire common midpoint reflection data. Thereafter, a processing workflow was applied to remove linear events interfering with the target reflections and to correct amplitudes due to transmission losses, source/receiver directivity, and geometric spreading effects. Finally, we investigated the thin-layer targets near incidence angle amplitude and the AVO response. The results showed that the interference between the primary PP reflections and the locally converted shear waves may considerably affect the observed amplitude response. The source wavelet bandwidth appeared as a second-order effect, and the internal multiple reflections were practically negligible. These results suggested that in real data sets, it is important to investigate the wave propagation modes and source wavelet role in the amplitudes observed, before deciding the AVO analysis/inversion workflow that should be adopted.

scholarly journals Ground-penetrating radar theory and application of thin-bed offset-dependent reflectivity

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. K47-K57 ◽  
Author(s):  
John H. Bradford ◽  
Jacob C. Deeds
Keyword(s):  
Ground Penetrating Radar ◽  
Transverse Electric ◽  
Transverse Magnetic ◽  
Stratified Medium ◽  
Contaminated Site ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Avo Analysis ◽  
Characteristic Wavelength ◽  
Ground Penetrating

Offset-dependent reflectivity or amplitude-variation-with-offset (AVO) analysis of ground-penetrating radar (GPR) data may improve the resolution of subsurface dielectric permittivity estimates. A horizontally stratified medium has a limiting layer thickness below which thin-bed AVO analysis is necessary. For a typical GPR signal, this limit is approximately 0.75 of the characteristic wavelength of the signal. Our approach to modeling the GPR thin-bed response is a broadband, frequency-dependent computation that utilizes an analytical solution to the three-interface reflectivity and is easy to implement for either transverse electric (TE) or transverse magnetic (TM) polarizations. The AVO curves for TE and TM modes differ significantly. In some cases, constraining the interpretation using both TE and TM data is critical. In two field examples taken from contaminated-site characterization data, we find quantitative thin-bed modeling agrees with the GPR field data and available characterization data.

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