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

2015 ◽  
Vol 3 (3) ◽  
pp. SZ15-SZ26 ◽  
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.

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.

Three-term amplitude-variation-with-offset projections

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. N51-N65 ◽  
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.

scholarly journals Extended poroelastic impedance

Geophysics ◽  
2019 ◽  
Vol 84 (2) ◽  
pp. N1-N14 ◽  
Author(s):  
Brian H. Russell ◽  
Ken J. Hedlin
Keyword(s):  
Incidence Angle ◽  
Elastic Parameter ◽  
P Wave ◽  
Rock Properties ◽  
New Approach ◽  
Amplitude Variation With Offset ◽  
The Earth ◽  
Band Limited ◽  
Elastic Impedance ◽  
Poroelastic Theory

Linearized approximations to the P-wave reflectivity as a function of the incidence angle (called amplitude variation with offset) involve the extraction of band-limited reflectivity terms that are a function of changes in the elastic constants of the earth across each lithologic interface. The most common of these extracted reflectivities are the intercept and gradient, usually labeled [Formula: see text] and [Formula: see text], respectively. The extended elastic impedance (EEI) method uses a rotation angle [Formula: see text] to map [Formula: see text] and [Formula: see text] into a new reflectivity corresponding to a particular elastic parameter. The success of EEI depends on finding an optimum value for the angle [Formula: see text]. This value is usually calculated by correlating the EEI result over a range of [Formula: see text] angles with various elastic parameters and then finding the best correlation coefficient. We have developed a new approach for the interpretation of the EEI method, which incorporates the Biot-Gassmann poroelastic theory and attaches a physical meaning to the [Formula: see text] angle. We call this method extended poroelastic impedance (EPI). The main advantage of the EPI method is that the [Formula: see text] angle is now interpreted as a parameter that is dependent on the dry-rock properties of the reservoir, rather than a parameter whose value is estimated empirically. The method is evaluated by numerical and synthetic seismic examples and by application to field data from a gas sand reservoir.

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

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.

Effect of VS predictors on amplitude variation with offset response

Geophysics ◽  
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.

Deepwater reservoir heterogeneity delineation using rock physics and extended elastic impedance inversion: Nile Delta case study

2014 ◽  
Vol 2 (4) ◽  
pp. T205-T219 ◽  
Author(s):  
Ahmed Hafez ◽  
Folkert Majoor ◽  
John P. Castagna
Keyword(s):  
Nile Delta ◽  
Rock Physics ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Impedance Inversion ◽  
Net To Gross ◽  
Deepwater Channel ◽  
Static Connectivity ◽  
Elastic Impedance

Deepwater channel reservoirs in the Nile Delta are delineated using extended elastic impedance inversion (EEI). We used the following workflow: seismic spectral blueing, rock physics and amplitude variation with offset modeling, seismic EEI and interpretation of the inverted cubes in terms of geologic facies, net-to-gross ratio, and static connectivity among depositional geobodies. Three subenvironments within the targeted reservoir interval were recognized using a combination of shale volume and [Formula: see text]-inverted cubes. These were used to generate 3D geobodies and a net-pay thickness map that were used in turn to calculate reservoir volumetrics. The results from the workflow matched well logs and could thus be used to investigate the potential of nearby prospects that have the same geologic settings.

AVO polarization and hodograms: AVO strength and polarization product

Geophysics ◽  
2003 ◽  
Vol 68 (3) ◽  
pp. 849-862 ◽  
Author(s):  
Patrice Nsoga Mahob ◽  
John P. Castagna
Keyword(s):  
Linear Correlation ◽  
Anomalous Behavior ◽  
Polarization Angle ◽  
Polarization Method ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Alternative Approach ◽  
Angle Difference ◽  
Synthetic Modeling ◽  
Background Trend

An alternative approach to identifying amplitude‐variation‐with offset (AVO) anomalies is to consider the AVO polarization in the AVO intercept–AVO gradient (A‐B) plane. This method does not require deviations or separations from a background trend exhibited in traditional crossplots such as intercept‐gradient (A‐B) or near trace–far trace (N‐F). A benefit of the hodogram or polarization method is that the wavelet is taken into consideration. Crossplotted intercept and gradient are polarized along a “background trend” for nonanomalous events and at angles different from the “background trend” for anomalous events. This allows recognition of anomalous behavior otherwise buried in a background. Attributes resulting from this methodology include (1) the polarization angle, (2) the polarization angle difference, (3) the AVO strength, (4) the polarization product, and (5) the linear‐correlation coefficient. These different attributes can then be used to enhance AVO interpretation. Synthetic modeling for a succession of gas and brine layers encased in shale units indicates that the method can potentially be an effective hydrocarbon indicator. Application of the method to a real seismic dataset shows polarization anomalies associated with hydrocarbons.

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
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