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.

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.

The Shuey-Radon transform

Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. V197-V206 ◽  
Author(s):  
Ali Gholami ◽  
Milad Farshad
Keyword(s):  
Radon Transform ◽  
Seismic Data ◽  
Matching Pursuit ◽  
Real Data ◽  
Transform Domain ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Linear System Of Equations ◽  
Matching Pursuit Algorithm ◽  
Zero Offset

The traditional hyperbolic Radon transform (RT) decomposes seismic data into a sum of constant amplitude basis functions. This limits the performance of the transform when dealing with real data in which the reflection amplitudes include the amplitude variation with offset (AVO) variations. We adopted the Shuey-Radon transform as a combination of the RT and Shuey’s approximation of reflectivity to accurately model reflections including AVO effects. The new transform splits the seismic gather into three Radon panels: The first models the reflections at zero offset, and the other two panels add capability to model the AVO gradient and curvature. There are two main advantages of the Shuey-Radon transform over similar algorithms, which are based on a polynomial expansion of the AVO response. (1) It is able to model reflections more accurately. This leads to more focused coefficients in the transform domain and hence provides more accurate processing results. (2) Unlike polynomial-based approaches, the coefficients of the Shuey-Radon transform are directly connected to the classic AVO parameters (intercept, gradient, and curvature). Therefore, the resulting coefficients can further be used for interpretation purposes. The solution of the new transform is defined via an underdetermined linear system of equations. It is formulated as a sparsity-promoting optimization, and it is solved efficiently using an orthogonal matching pursuit algorithm. Applications to different numerical experiments indicate that the Shuey-Radon transform outperforms the polynomial and conventional RTs.

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.

scholarly journals Nonstretching NMO correction of prestack time-migrated gathers using a matching-pursuit algorithm

Geophysics ◽  
2013 ◽  
Vol 78 (1) ◽  
pp. U9-U18 ◽  
Author(s):  
Bo Zhang ◽  
Kui Zhang ◽  
Shiguang Guo ◽  
Kurt J. Marfurt
Keyword(s):  
Matching Pursuit ◽  
Amplitude Variation With Offset ◽  
Seismic Resolution ◽  
Long Offset ◽  
Analysis Workflow ◽  
Nmo Correction ◽  
Data Volume ◽  
Matching Pursuit Algorithm ◽  
Normal Moveout Correction ◽  
Nmo Stretch

Wide-azimuth, long-offset surveys are becoming increasingly common in unconventional exploration plays where one of the key routine processes is maintaining data fidelity at far offsets. The conventional NMO correction that processes the data sample-by-sample results in the well-known decrease of frequency content and amplitude distortion through stretch, which lowers the seismic resolution and hinders [Formula: see text] and amplitude variation with offset and azimuth (AVAz) analysis of the long-offset signal. To mitigate the stretch typically associated with large offsets, we use a matching-pursuit-based normal moveout correction (MPNMO) to reduce NMO-stretch effects in long-offset data. MPNMO corrects the data wavelet-by-wavelet rather than sample-by-sample, thereby avoiding stretch. We apply our technique (1) to a set of synthetic gathers and (2) as part of a residual velocity analysis workflow to a prestack time-migrated data volume acquired over the Northern Chicontepec Basin, Mexico. Test results show that MPNMO can produce relatively nonstretched events and generate higher temporal resolution prestack gathers.

AVO-sensitive semblance analysis for wide-azimuth data

Geophysics ◽  
2008 ◽  
Vol 73 (2) ◽  
pp. U1-U11 ◽  
Author(s):  
Jia Yan ◽  
Ilya Tsvankin
Keyword(s):  
Azimuthal Anisotropy ◽  
Polarity Reversal ◽  
Inversion Algorithm ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Reflection Data ◽  
Long Offset ◽  
Class 1 ◽  
Polarity Reversals ◽  
Analysis Models

Conventional semblance-based moveout analysis models prestack reflection data with events that have hyperbolic move-out and no amplitude variation with offset (AVO). Substantial amplitude variation and even phase change with offset do not significantly compromise the semblance operator. However, polarity reversal associated with a change in the sign of the reflection coefficient may cause conventional semblance to fail. An existing modification of the semblance operator that takes amplitude variations into account (so-called AK semblance) is limited to narrow-azimuth data and cannot handle nonhyperbolic moveout at large offsets. We employ a 3D nonhyperbolic moveout inversion algorithm to extend the AK semblance method to wide-azimuth data recorded on long spreads. To preserve velocity resolu-tion, the ratio [Formula: see text] of the AVO gradient and intercept is kept constant within each semblance window. In the presence of azimuthal anisotropy, however, the parameter [Formula: see text] has to be azimuthally dependent. Synthetic tests confirm that distortions in moveout analysis caused by polarity reversals become more common for long-offset data. Conventional semblance produces substantial errors in the NMO ellipse and azimuthally varying anellipticity parameter [Formula: see text] not just for class 2 AVO response but also for some models with class 1 AVO. In contrast, the AK semblance algorithm gives accurate estimates of the moveout parameters even when the position of the polarity reversal varies with azimuth. The AK method not only helps to flatten wide-azimuth reflection events prior to stacking and azimuthal AVO analysis but also provides input parameters for the anisotropic geometrical-spreading correction.

Fracture mapping using seismic amplitude variation with offset and azimuth analysis at the Weyburn CO2 storage site

Geophysics ◽  
2012 ◽  
Vol 77 (6) ◽  
pp. B295-B306 ◽  
Author(s):  
Alexander Duxbury ◽  
Don White ◽  
Claire Samson ◽  
Stephen A. Hall ◽  
James Wookey ◽  
...  
Keyword(s):  
Cross Sections ◽  
Co2 Storage ◽  
Horizontal Stress ◽  
Storage Site ◽  
Fracture Zones ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Seal Integrity ◽  
Cap Rock ◽  
Weyburn Field

Cap rock integrity is an essential characteristic of any reservoir to be used for long-term [Formula: see text] storage. Seismic AVOA (amplitude variation with offset and azimuth) techniques have been applied to map HTI anisotropy near the cap rock of the Weyburn field in southeast Saskatchewan, Canada, with the purpose of identifying potential fracture zones that may compromise seal integrity. This analysis, supported by modeling, observes the top of the regional seal (Watrous Formation) to have low levels of HTI anisotropy, whereas the reservoir cap rock (composite Midale Evaporite and Ratcliffe Beds) contains isolated areas of high intensity anisotropy, which may be fracture-related. Properties of the fracture fill and hydraulic conductivity within the inferred fracture zones are not constrained using this technique. The predominant orientations of the observed anisotropy are parallel and normal to the direction of maximum horizontal stress (northeast–southwest) and agree closely with previous fracture studies on core samples from the reservoir. Anisotropy anomalies are observed to correlate spatially with salt dissolution structures in the cap rock and overlying horizons as interpreted from 3D seismic cross sections.

The impact of reservoir scale on amplitude variation with offset

2016 ◽  
Vol 65 (3) ◽  
pp. 736-746 ◽  
Author(s):  
Chao Xu ◽  
Jianxin Wei ◽  
Bangrang Di
Keyword(s):  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
The Impact

Information on elastic parameters obtained from the amplitudes of reflected waves

Geophysics ◽  
1995 ◽  
Vol 60 (5) ◽  
pp. 1426-1436 ◽  
Author(s):  
Wojciech Dȩbski ◽  
Albert Tarantola
Keyword(s):  
Mass Density ◽  
Seismic Velocities ◽  
Elastic Parameters ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Reflected Waves ◽  
Seismic Amplitude ◽  
Earth Models ◽  
Definition Of ◽  
Proper Analysis

Seismic amplitude variation with offset data contain information on the elastic parameters of geological layers. As the general solution of the inverse problem consists of a probability over the space of all possible earth models, we look at the probabilities obtained using amplitude variation with offset (AVO) data for different choices of elastic parameters. A proper analysis of the information in the data requires a nontrivial definition of the probability defining the state of total ignorance on different elastic parameters (seismic velocities, Lamé’s parameters, etc.). We conclude that mass density, seismic impedance, and Poisson’s ratio constitute the best resolved parameter set when inverting seismic amplitude variation with offset data.

Model misspecification and bias in the least-squares algorithm: Implications for linearized isotropic AVO

2021 ◽  
Vol 40 (9) ◽  
pp. 646-654
Author(s):  
Henning Hoeber
Keyword(s):  
Least Squares ◽  
Model Misspecification ◽  
Forward Model ◽  
Model Parameters ◽  
Omitted Variables ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Omitted Variable Bias ◽  
Least Squares Fit ◽  
Variable Bias

When inversions use incorrectly specified models, the estimated least-squares model parameters are biased. Their expected values are not the true underlying quantitative parameters being estimated. This means the least-squares model parameters cannot be compared to the equivalent values from forward modeling. In addition, the bias propagates into other quantities, such as elastic reflectivities in amplitude variation with offset (AVO) analysis. I give an outline of the framework to analyze bias, provided by the theory of omitted variable bias (OVB). I use OVB to calculate exactly the bias due to model misspecification in linearized isotropic two-term AVO. The resulting equations can be used to forward model unbiased AVO quantities, using the least-squares fit results, the weights given by OVB analysis, and the omitted variables. I show how uncertainty due to bias propagates into derived quantities, such as the χ-angle and elastic reflectivity expressions. The result can be used to build tables of unique relative rock property relationships for any AVO model, which replace the unbiased, forward-model results.

An integrated broadband preprocessing method for towed-streamer seismic data

Geophysics ◽  
2020 ◽  
Vol 85 (2) ◽  
pp. V201-V221 ◽  
Author(s):  
Mehdi Aharchaou ◽  
Erik Neumann
Keyword(s):  
Seismic Data ◽  
High Frequency ◽  
Pressure Data ◽  
Amplitude Variation ◽  
Field Source ◽  
Amplitude Variation With Offset ◽  
Ringing Artifacts ◽  
Joint Application ◽  
Amplitude Compensation ◽  
Unified Method

Broadband preprocessing has become widely used for marine towed-streamer seismic data. In the standard workflow, far-field source designature, receiver and source-side deghosting, and redatuming to mean sea level are applied in sequence, with amplitude compensation for background [Formula: see text] delayed until the imaging or postmigration stages. Thus, each step is likely to generate its own artifacts, quality checking can be time-consuming, and broadband data are only obtained late in this chained workflow. We have developed a unified method for broadband preprocessing — called integrated broadband preprocessing (IBP) — which enables the joint application of all the above listed steps early in the processing sequence. The amplitude, phase, and amplitude-variation-with-offset fidelity of IBP are demonstrated on pressure data from the shallow, deep, and slanted streamers. The integration allows greater sparsity to emerge in the representation of seismic data, conferring clear benefits over the sequential application. Moreover, time sparsity, full dimensionality, and early amplitude [Formula: see text] compensation all have an impact on broadband data quality, in terms of reduced ringing artifacts, improved wavelet integrity at large crossline angles, and fewer residual high-frequency multiples.

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