Analysis of azimuthal variation in<i>P</i>‐wave signature from orthogonal streamer lines

Liu, Yi hyphen; Jie, Jie; Li, Xiang‐Yang; Yang, Rong-Jia; MacBeth, Colin; Anderton, P.W.

doi:10.1190/1.1820935

Cited by 4 publications

(5 citation statements)

References 6 publications

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“…The physical model consists of only a single set of fractures. Numerical modelling of wave propagation in such a medium predicts that the P ‐wave seismic attributes, such as traveltime, velocity and reflected wave amplitude will vary with azimuth, diagnostic of fracture‐induced anisotropy (Liu et al 2000b; Hall & Kendall 2003). To verify this, we examine the azimuthal variations in P ‐wave attributes for both models.…”

Section: Azimuthal Variations Of P‐wave Attributesmentioning

confidence: 99%

“…Numerical modelling also predicts that azimuthal variations of the P ‐wave attributes can be approximately described by an ellipse, as shown in Liu et al (2000b) and Liu (2003). For velocity variation, the long axis of the ellipse indicates the fracture strike, and the ratio of the short to long axis is proportional to the fracture density.…”

Section: Azimuthal Variations Of P‐wave Attributesmentioning

confidence: 99%

“…Both numerical modelling and case histories of fracture detection using P ‐wave seismic have been the subject of intensive study (e.g. Lynn et al 1996; Liu et al 2000b; Smith & McGarrity 2001; Hall & Kendall 2003; Wang & Li 2006, amongst others). In comparison, the number of corresponding physical‐modelling studies is much less (Luo & Evans 2004), whilst physical modelling studies of shear wave splitting were well documented in the early 1990s (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Physical modelling studies of 3-DP-wave seismic for fracture detection

Wang

Qian

et al. 2007

Geophysical Journal International

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S U M M A R YWe have carried out two seismic physical experiments to acquire wide-azimuth P-wave 3-D seismic data with a scaled down model (1:10 000) and scaled-up frequencies (10 000:1). Our aims are to verify the physical basis of using P-wave attributes for fracture detection, to understand the usage of these attributes and their merits, and to investigate the effects of acquisition geometry and structural variations on these attributes. The base model consists of a fractured layer sandwiched between two isotropic layers (Epoxylite). Inside the fractured layer there is a dome and a fault block for investigating the effects of structural variations. The two experiments were carried out using different acquisition geometries. The first experiment was conducted to maximize the data quality, with an offset-depth ratio of only 0.68 to the bottom of the fracture layer. For comparison, the second experiment was carried out to maximize the anisotropy effects, with the offset-depth ratio to the bottom of the fracture layer raised to 1.34.For each experiment, about 20 km 2 of wide-azimuth 3-D data were acquired with a P-wave source. The physical modelling confirms that the P-wave attributes (traveltime, amplitude and velocity) exhibit azimuthal variations diagnostic of fracture-induced anisotropy. For the first experiment with noise-free data, the amplitude from the top of the fracture layer yields the best results that agree with the physical model parameters and free of the acquisition footprint. The results from other attributes (traveltime, velocity, AVO gradient) are either contaminated by the structural imprint, or by the acquisition footprint due to the lack of offset coverage. For the second experiment, despite the interferences from multiples and other coherent noise, the traveltime attributes yield the best results; both the acquisition footprint and the structural imprint are reduced due to the increased offset coverage. However, the results from the amplitudes are affected by the noise and are less reliable. Analysis of the two experiments reveals that the offset-depth ratio to the target is a key parameter for the success of the P-wave techniques. Smaller offset-depth coverage may only be applicable to amplitude attributes with high quality data; whilst large offset coverage makes it possible to use traveltime attributes. A reliable estimation from traveltime attributes requires an offset-depth ratio of 1.0 or more.

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Section: Azimuthal Variations Of P‐wave Attributesmentioning

confidence: 99%

Section: Azimuthal Variations Of P‐wave Attributesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Physical modelling studies of 3-DP-wave seismic for fracture detection

Wang

Qian

et al. 2007

Geophysical Journal International

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“…Both numerical modeling and case history of fracture detection using P-wave seismic have been the subject of intensive study (e.g. Lynn et al, 1996;Liu et al, 2000;Hall et al, 2000;Smith and McGarrity, 2001; amongst others). However, few studies have verified these techniques using physical experiment (Brown et al, 1991).…”

Section: Introductionmentioning

confidence: 99%

Fracture detection using 3D seismic data: A physical modeling study

Wang¹,

Li²

2003

SEG Technical Program Expanded Abstracts 2003

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A seismic physical experiment has been conducted to acquire wide-azimuth P-wave 3D seismic data with a scaled down model (1:10000) and scaled-up frequencies (10000:1). Our aim is to verify the physical basis of using P-wave attributes for fracture detection and to understand the usage of these attributes and their merits. The model consists of a fractured layer (artificial limestone) sandwiched between two isotropic layers (Epoxylite). Inside the fractured layer there is a dome and a fault block for investigating the effects of structural variations. About 20 km 2 of wide-azimuth 3D data was acquired with a Pwave source. The physical modeling confirms that the Pwave attributes (traveltime, amplitude and velocity) exhibit azimuthal variations diagnostic of fracture-induced anisotropy. Two processing techniques are used to extract the fracture information: full-azimuth surface fitting and narrow-azimuth stacking. The results show that the commonly used narrow-azimuth stacking technique may enhance the acquisition footprint. The final fracture orientation and intensity maps estimated using the surfacefitting method agree with the physical model parameters.

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“…Mallick and Frazer, 1991Lefeuvre, 1994Lynn et al, 1997Ramos and Davis, 1997P erez et al, 1999) and many methods have been developed(e.g. Li, 1997Liu et al, 1999. However, these methods assume that distinct re ections from the top and bottom of reservoirs can be clearly identi ed.…”

Section: Introductionmentioning

confidence: 99%

Characterization of azimuthal anisotropy in the presence of thin layers using P‐Waves

Liu

et al. 2001

SEG Technical Program Expanded Abstracts 2001

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In this paper, we study the e ect of thin layers on the AVAZ analysis using synthetic modelling. A range of models are constructed by sandwiching a thin-layered reservoir with di erent t h i c kness between two isotropic layers. Azimuthal gathers are calculated for each of these thin-layered models. After we apply azimuthal AVO analysis to the synthetics, we nd that fracture orientation and intensity can be estimated accurately if the thickness of the thin layer is larger than a quarter of the wavelength. However, there are large discrepancies in the orientation and intensity estimates. We nally present a new procedure to improve the detectability of azimuthal anisotropy in the presence of thin layers.

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Analysis of azimuthal variation inP‐wave signature from orthogonal streamer lines

Cited by 4 publications

References 6 publications

Physical modelling studies of 3-DP-wave seismic for fracture detection

Physical modelling studies of 3-DP-wave seismic for fracture detection

Fracture detection using 3D seismic data: A physical modeling study

Characterization of azimuthal anisotropy in the presence of thin layers using P‐Waves

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