Amplitude variation with offset (AVO) analysis via fluid replacement modeling (FRM) for characterizing the reservoir response of Cretaceous sand interval

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

Geophysics ◽

10.1190/1.1444417 ◽

1998 ◽

Vol 63 (4) ◽

pp. 1177-1183 ◽

Cited By ~ 47

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.

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Overburden dependent AVA inversion

Geophysics ◽

10.1190/1.3332529 ◽

2010 ◽

Vol 75 (2) ◽

pp. C15-C23 ◽

Cited By ~ 2

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.

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Fracture clustering effect on amplitude variation with offset and azimuth analyses

Geophysics ◽

10.1190/geo2016-0045.1 ◽

2017 ◽

Vol 82 (1) ◽

pp. N13-N25 ◽

Cited By ~ 20

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.

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Determining the coal bed methane distribution based on Amplitude Variation with Offset (AVO) analysis and seismic inversion: case study of Sumatra Basin

10.29118/ipa.2421.07.g.064 ◽

2018 ◽

Author(s):

P.H. Wibawa

Keyword(s):

Seismic Inversion ◽

Coal Bed ◽

Coal Bed Methane ◽

Amplitude Variation ◽

Amplitude Variation With Offset ◽

Avo Analysis ◽

Methane Distribution

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

Geophysics ◽

10.1190/geo2016-0262.1 ◽

2017 ◽

Vol 82 (4) ◽

pp. N27-N41 ◽

Cited By ~ 5

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.

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

Geophysics ◽

10.1190/1.2194524 ◽

2006 ◽

Vol 71 (3) ◽

pp. K47-K57 ◽

Cited By ~ 57

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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Amplitude variation with offset analysis of time-lapse land seismic data in a gas field, Thrace Basin, Turkey

Interpretation ◽

10.1190/int-2015-0186.1 ◽

2016 ◽

Vol 4 (4) ◽

pp. T543-T556

Author(s):

Sait Baytok ◽

Şeref Arzu Aktepe ◽

Muhlis Ünaldi

Keyword(s):

Seismic Data ◽

Time Lapse ◽

Amplitude Variation ◽

Amplitude Variation With Offset ◽

Data Cubes ◽

Avo Analysis ◽

Thrace Basin ◽

Northwestern Turkey ◽

4D Seismic ◽

Monitor Data

The Thrace Basin that is located in northwestern Turkey contains sandstone and carbonate reservoirs of Eocene and Oligocene age. Production and exploration activities are still underway. Mapping undrained sweet spots from seismic data is currently a challenge, so time lapse (4D) seismic is used to reduce the risk for new production and development drilling. We have evaluated the normalization and amplitude variation with offset (AVO) analysis of 3D-4D land seismic data in a gas producing field from which baseline and monitor surveys were acquired in 2002 and 2011, respectively. Through AVO analysis, intercept (A) and gradient (B) analysis was conducted, and fluid factor (FF) attribute maps were generated for the assessment of the remaining potential areas. Synthetic gathers were created for simulation of the AVO response, drained and undrained stages and compared with the corresponding 4D seismic data. The drainage of gas from the reservoir interval is evident from the difference maps between 2002 and 2011 seismic data. Both data sets were processed using an amplitude friendly processing sequence. This parallel processing was followed a mild data conditioning and crossequalization for reliable 4D interpretation. The 4D seismic data, especially land data, has low repeatability and requires conditioning to reduce the 4D noise. The 4D noise can be described as nonrepeatable noise, and any difference outside the reservoir zone is not related to production. A so-called crossequalization was applied to the base and the monitor data to bring out similarities so that they cancel out when differences of seismic data and its attributes indicated only the production results over the reservoir zones. As the available 4D data crossequalization software was implemented for stack data only, we created angle band stacks and crossequalized each angle band stack from the base and the monitor data cubes. Five angle band stacks from the base and the monitor prestack data cubes 0°–55° (0°–15°, 15°–25°, 25°–35°, 35°–45°, and 45°–55°) were crossequalized individually. The crossequalized angle band stacks were used in AVO analysis and AVO inversion to generate pore fill identifiers such as FF to map possible undrained zones after 10 years of production.

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Effective AVO crossplot modeling: A tutorial

Geophysics ◽

10.1190/1.1444769 ◽

2000 ◽

Vol 65 (3) ◽

pp. 700-711 ◽

Cited By ~ 30

Author(s):

Christopher P. Ross

Keyword(s):

Seismic Data ◽

Well Logs ◽

Substitution Effects ◽

High Grade ◽

Amplitude Variation ◽

Amplitude Variation With Offset ◽

Avo Analysis ◽

Fundamental Process ◽

Seismic Volumes ◽

Selection Of

The ability to crossplot attributes from a 3-D seismic volume permits a geophysicist to identify and high grade subsets of the 3-D volume that warrant detailed inspection. In the case of amplitude‐variation‐with‐offset (AVO) crossplotting, the seismic attributes are derived from CDP data. Crossplotting has become a fundamental process in AVO analysis, just as it is in petrophysical analysis. Comprehending the intricacies and selection of attributes is essential for successful AVO analysis and improved seismic interpretation. AVO crossplotting of modeled seismic data derived from well logs with the Biot‐Gassmann equations provides a basis for understanding fluid substitution effects on AVO attribute interactions when crossplotting. With these model‐based understandings, improved multi‐attribute interpretation processes can commence with AVO crossplotting of seismic volumes.

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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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