The effect of rock properties in the analysis of amplitude variation with offset (AVO) on Baturaja carbonates formation at the northern part of West Java Basin

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.

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Three-term amplitude-variation-with-offset projections

Geophysics ◽

10.1190/geo2017-0763.1 ◽

2018 ◽

Vol 83 (5) ◽

pp. N51-N65 ◽

Cited By ~ 3

Author(s):

Vaughn Ball ◽

Luis Tenorio ◽

Christian Schiøtt ◽

Michelle Thomas ◽

J. P. Blangy

Keyword(s):

Rock Physics ◽

Projection Methods ◽

Well Logs ◽

Rock Properties ◽

Inversion Method ◽

Practical Implementation ◽

Angle Of Incidence ◽

Amplitude Variation ◽

Amplitude Variation With Offset ◽

Maximum Angle

A three-term (3T) amplitude-variation-with-offset projection is a weighted sum of three elastic reflectivities. Parameterization of the weighting coefficients requires two angle parameters, which we denote by the pair [Formula: see text]. Visualization of this pair is accomplished using a globe-like cartographic representation, in which longitude is [Formula: see text], and latitude is [Formula: see text]. Although the formal extension of existing two-term (2T) projection methods to 3T methods is trivial, practical implementation requires a more comprehensive inversion framework than is required in 2T projections. We distinguish between projections of true elastic reflectivities computed from well logs and reflectivities estimated from seismic data. When elastic reflectivities are computed from well logs, their projection relationships are straightforward, and they are given in a form that depends only on elastic properties. In contrast, projection relationships between reflectivities estimated from seismic may also depend on the maximum angle of incidence and the specific reflectivity inversion method used. Such complications related to projections of seismic-estimated elastic reflectivities are systematized in a 3T projection framework by choosing an unbiased reflectivity triplet as the projection basis. Other biased inversion estimates are then given exactly as 3T projections of the unbiased basis. The 3T projections of elastic reflectivities are connected to Bayesian inversion of other subsurface properties through the statistical notion of Bayesian sufficiency. The triplet of basis reflectivities is computed so that it is Bayes sufficient for all rock properties in the hierarchical seismic rock-physics model; that is, the projection basis contains all information about rock properties that is contained in the original seismic.

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A comparison of competing amplitude variation with offset techniques applied to tight gas sand exploration in the Cooper Basin of Australia

Interpretation ◽

10.1190/int-2014-0262.1 ◽

2015 ◽

Vol 3 (3) ◽

pp. SZ15-SZ26 ◽

Cited By ~ 2

Author(s):

Stephanie Tyiasning ◽

Dennis Cooke

Keyword(s):

Random Noise ◽

Class I ◽

Rock Properties ◽

Tight Gas ◽

Amplitude Variation ◽

Amplitude Variation With Offset ◽

Optimal Rotation ◽

Elastic Impedance ◽

Synthetic Modeling ◽

Cooper Basin

We have developed a tight gas amplitude variation with offset (AVO) case history from the Cooper Basin of Australia that addressed the exploration problem of mapping thin fluvial tight gas sand bodies. In the Cooper Basin, Permian Toolachee and Patchawarra sands are difficult to interpret on seismic data due to strong reflections from adjacent Permian coals. This is not the common AVO problem of distinguishing between coal and gas sand, but a more difficult class-I AVO problem of mapping fluvial sands beneath a sheet coal that varies in thickness. We have reviewed local rock properties and concluded that Poisson’s ratio is probably the most appropriate rock property to solve the above exploration problem. We have compared various seismic attributes made using the extended elastic impedance (EEI) technique and a rotation of near and far partial stacks. In a synthetic modeling study that included random noise and tuning, we compared the noise-discrimination abilities of three competing AVO crossplot techniques and “rotated” the attributes made from them. These three crossplots were as follows: intercept versus gradient (I-G), full-stack versus far-minus-near (Full-FmN), and near-stack versus far-stack (N-F). Previous papers on this subject have found that (I-G) crossplots had a spurious correlation in the presence of noise that did not occur with the (Full-FmN) and (N-F) crossplots. We found that for our class-I AVO case, (1) the advantage of the (Full-FmN) and (N-F) crossplots disappeared in the presence of tuning, (2) if tuning was present, the optimal rotation angle was determined by the “tuning angle,” not by the noise angle or some desired EEI angle, and (3) if the three different crossplots were rotated by their respective “tuning” angles, the results were identical.

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Seismic reservoir characterization of a class-1 amplitude variation with offset turbiditic system located offshore Cote d’Ivoire, West Africa

Interpretation ◽

10.1190/int-2017-0163.1 ◽

2018 ◽

Vol 6 (2) ◽

pp. SD115-SD128

Author(s):

Pedro Alvarez ◽

William Marin ◽

Juan Berrizbeitia ◽

Paola Newton ◽

Michael Barrett ◽

...

Keyword(s):

West Africa ◽

Seismic Data ◽

Reservoir Characterization ◽

Rock Physics ◽

Rock Properties ◽

Well Log ◽

Amplitude Variation ◽

Amplitude Variation With Offset ◽

Fluid Content ◽

Class 1

We have evaluated a case study, in which a class-1 amplitude variation with offset (AVO) turbiditic system located offshore Cote d’Ivoire, West Africa, is characterized in terms of rock properties (lithology, porosity, and fluid content) and stratigraphic elements using well-log and prestack seismic data. The methodology applied involves (1) the conditioning and modeling of well-log data to several plausible geologic scenarios at the prospect location, (2) the conditioning and inversion of prestack seismic data for P- and S-wave impedance estimation, and (3) the quantitative estimation of rock property volumes and their geologic interpretation. The approaches used for the quantitative interpretation of these rock properties were the multiattribute rotation scheme for lithology and porosity characterization and a Bayesian lithofluid facies classification (statistical rock physics) for a probabilistic evaluation of fluid content. The result indicates how the application and integration of these different AVO- and rock-physics-based reservoir characterization workflows help us to understand key geologic stratigraphic elements of the architecture of the turbidite system and its static petrophysical characteristics (e.g., lithology, porosity, and net sand thickness). Furthermore, we found out how to quantify and interpret the risk related to the probability of finding hydrocarbon in a class-1 AVO setting using seismically derived elastic attributes, which are characterized by having a small level of sensitivity to changes in fluid saturation.

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Effect of VS predictors on amplitude variation with offset response

Geophysics ◽

10.1190/geo2017-0259.1 ◽

2018 ◽

Vol 83 (1) ◽

pp. N1-N13

Author(s):

Humberto S. Arévalo-López ◽

Uri Wollner ◽

Jack P. Dvorkin

Keyword(s):

Seismic Data ◽

Poor Quality ◽

Rock Properties ◽

Specific Situation ◽

S Wave ◽

Amplitude Variation ◽

Amplitude Variation With Offset ◽

Seismic Amplitude ◽

Text Prediction ◽

A Site

We have posed a question whether the differences between various [Formula: see text] predictors affect one of the ultimate goals of [Formula: see text] prediction, generating synthetic amplitude variation with offset (AVO) gathers to serve as a calibration tool for interpreting the seismic amplitude for rock properties and conditions. We address this question by evaluating examples in which we test several such predictors at an interface between two elastic layers, at pseudowells, and at a real well with poor-quality S-wave velocity data. The answer based on the examples presented is that no matter which [Formula: see text] predictor is used, the seismic responses at a reservoir are qualitatively identical. The choice of a [Formula: see text] predictor does not affect our ability (or inability) to forecast the presence of hydrocarbons from seismic data. We also find that the amplitude versus angle responses due to different predictors consistently vary along the same pattern, no matter which predictor is used. Because our analysis uses a “by-example” approach, the conclusions are not entirely general. However, the method of comparing the AVO responses due to different [Formula: see text] predictors discussed here is. Hence, in a site-specific situation, we recommend using several relevant predictors to ascertain whether the choice significantly affects the synthetic AVO response and if this response is consistent with veritable seismic data.

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

Geophysics ◽

10.1190/geo2011-0075.1 ◽

2012 ◽

Vol 77 (6) ◽

pp. B295-B306 ◽

Cited By ~ 17

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.

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The impact of reservoir scale on amplitude variation with offset

Geophysical Prospecting ◽

10.1111/1365-2478.12431 ◽

2016 ◽

Vol 65 (3) ◽

pp. 736-746 ◽

Cited By ~ 1

Author(s):

Chao Xu ◽

Jianxin Wei ◽

Bangrang Di

Keyword(s):

Amplitude Variation ◽

Amplitude Variation With Offset ◽

The Impact

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Information on elastic parameters obtained from the amplitudes of reflected waves

Geophysics ◽

10.1190/1.1443877 ◽

1995 ◽

Vol 60 (5) ◽

pp. 1426-1436 ◽

Cited By ~ 73

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.

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

The Leading Edge ◽

10.1190/tle40090646.1 ◽

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.

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An integrated broadband preprocessing method for towed-streamer seismic data

Geophysics ◽

10.1190/geo2019-0521.1 ◽

2020 ◽

Vol 85 (2) ◽

pp. V201-V221 ◽

Cited By ~ 2

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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