Detection of fracture orientation using azimuthal variation of<i>P</i>-wave AVO responses

Perez, Maria A.; Gibson, Richard L.; Toksöz, M. Nafi

doi:10.1190/1.1444632

Cited by 57 publications

(19 citation statements)

References 26 publications

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“…Sena & Toksöz 1993). More importantly, however, the effects of seismic anisotropy can be used to infer fracture orientation, as well as locations of intense fracturing in the subsurface (Pérez et al 1999;Angerer et al 2002;Bakulin et al 2002;Shen et al 2002;Luo & Evans 2004;Grechka & Kachanov 2006;Zeidouni & van Kruijsdijk 2006;Liu et al 2007;Perez & Marfurt 2008;Sayers & den Boer 2012;Aminzadeh et al 2013;Far et al 2013). These results provide important constraints for the development of fluid flow models for reservoir management.…”

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confidence: 95%

An effective medium model for the stress-dependence of anisotropic seismic velocities in fractured rock

Gibson

Gao

2014

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Reliable analysis of time-lapse seismic data to detect movements of pore fluids requires consideration of variations in subsurface stress as well as fluid saturations. Achieving this goal requires reliable rock physics models that relate these stress changes to seismic velocity. Although there are many theories for the effective elastic properties of fractured media, only a small number directly include stress-dependence. Therefore, we have developed a new model that provides expressions that are comparatively easy to work with and requires estimation of only a small number of parameters. In this paper, we apply this model for the first time to the inversion of published laboratory measurements of pressure-dependent anisotropic seismic velocities. Specifically, we utilize measured velocities in two orthogonal directions to estimate the model parameters for a transversely isotropic medium. The model is then used to predict directional velocity variation in other directions at ambient pressure, and the errors in all cases are small. Synthetic shear wave seismograms computed for a hypothetical carbonate reservoir model show the changes in shear wave splitting and travel times that are predicted when seismic properties are computed using the theoretical model and help to illustrate the potential applications of the theoretical model to reservoir characterization.

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confidence: 95%

An effective medium model for the stress-dependence of anisotropic seismic velocities in fractured rock

Gibson

Gao

2014

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“…A 1-kg explosive charge at 10 m depth was used for the source. The shotpoint spacing was 51 m, and the source offset was 17 m. The nearest offset was 17 m and the farthest offset was 3650 m, equivalent to an incidence angle of 32' for the target zone (Perez, 1997). The maximum fold was 33 traces.…”

Section: Seismic Datamentioning

confidence: 99%

Azimuthal offset‐dependent attributes applied to fracture detection in a carbonate reservoir

et al. 2002

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Offset-dependent attributes-amplitude versus offset (AVO) and frequency versus offset-are extracted from 2-D P-wave seismic data using the multiple signal classification technique. These attributes are used to detect fracture orientation in a carbonate reservoir located in the Maporal field in the Barinas basin of southwestern Venezuela. In the fracture normal direction, P-wave reflectivity is characterized by a large increase of amplitude with offset (large positive AVO gradient) and a large decrease of frequency with offset (large negative frequency versus offset gradient). In the fracture strike direction, P-wave reflectivity shows a scattered variation in AVO but a small variation in frequency with offset. Our results also show that the reservoir heterogeneity can lead to large variations of AVO signatures and that using azimuthal offset-dependent frequency attributes can help lessen the ambiguity when detecting fracture orientation.

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“…Saturated fluid contents are expected to be water and oil in the reservoir. The API number of crude oil (American Petroleum Institute oil gravity) is 28 (Perez, 1997). Oil density and modulus are calculated based on Batzle and Wang (1992).…”

Section: Azimuthal Avo and Fvo Analysesmentioning

confidence: 99%

Azimuthal offset‐dependent attributes (AVO and FVO) applied to fracture detection

Shen¹,

Sierra²,

Burns³

et al. 1999

SEG Technical Program Expanded Abstracts 1999

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Using the amplitude versus offset (AVO) and the frequency versus offset (FVO) information, the diagnostic ability of P-wave seismic data in fracture detection is investigated. The offset-dependent attributes (AVO and FVO) are estimated by using an eigenvector based estimation technique, the multiple signal classification frequency estimator. These attributes are applied to the determination of principal orientation of fractures in carbonate fractured reservoirs located in the Maporal field in the Barinas basin of southwestern Venezuela. Our studies show that, in the crack normal direction, P-wave reflectivity is characterized by a large increase of amplitude with offset (large positive AVO gradient) and a large frequency decay with offset (large negative FVO gradient). In the crack strike direction, P-wave reflectivity is characterized by a wide range of AVO gradients but a small variation of FVO gradients. The analyses of inverted offsetdependent velocities and theoretical calculations show that the lateral heterogeneity in the reservoir zone can lead to large variations of AVO signatures. The offset-dependent frequency attribute can help lessen the ambiguity in fracture detection.. The combination of the offset-dependent frequency attribute is more beneficial than using the offset-dependent amplitude attribute alone.

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Detection of fracture orientation using azimuthal variation ofP-wave AVO responses

Cited by 57 publications

References 26 publications

An effective medium model for the stress-dependence of anisotropic seismic velocities in fractured rock

An effective medium model for the stress-dependence of anisotropic seismic velocities in fractured rock

Azimuthal offset‐dependent attributes applied to fracture detection in a carbonate reservoir

Azimuthal offset‐dependent attributes (AVO and FVO) applied to fracture detection

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