14. Case Studies of Multicomponent Seismic Data for Fracture Characterization: Austin Chalk Examples

Li, Xiangyang; Mueller, Mike

doi:10.1190/1.9781560802099.ch14

Cited by 14 publications

(4 citation statements)

References 41 publications

(72 reference statements)

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“…Several authors (e.g., Kuich, 1989;Li and Muller, 1997;Najmuddin, 2003) discuss the geology of the Giddings oil field as well as present seismic data from the field. The Giddings field, which is within the Austin Chalk (blue dotted outline, northeast of San Marcos Arch, Figure 1), is located some ∼80−112 km (50-70 mi) northeast of the nearest subsurface volcanic mound location in the Houston Embayment (Figure 1).…”

Section: Discussionmentioning

confidence: 99%

Diffraction imaging of polygonal faults within a submarine volcanic terrain, Maverick Basin, south Texas

2015

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Polygonal fault systems are common structural features of intracratonic continental margins. The map-view geometry of these faults became apparent with the use of powerful fault-imaging seismic attributes, such as coherence and curvature. However, these attributes lack the amplitude information necessary for lithological evaluation. We developed a 3D diffraction volume that not only imaged faults but also contained amplitude information. From the unmigrated stack volume, we extracted diffractions that were transformed into amplitude envelope and root-mean-square amplitude volumes. These attributes, together with clay volume (V clay ) data, were extracted along interpreted horizons and fault planes. Crossplots between seismic attributes and V clay enabled linear relationships between the attributes and V clay , which were used to infer lithological composition within fault zones. Our results found that, although the fault zones were clay filled, some subvertically inclined clay-poor zones that could serve as permeable pathways were present along the fault planes. In map view, images from diffraction volume were comparable with those obtained from coherence and curvature attributes; however, diffraction images appeared to be busy because of the huge number of diffracted waves embedded in the data. In addition, we found that, although V clay increases with increasing diffraction energy, no systematic relationship exists between V clay and curvature, or between V clay and coherence. As such, curvature and coherence cannot be used to predict lithological distribution within fault zones. Furthermore, we observed that the higher the diffraction energies, the higher the fluid saturation, suggesting higher impedance contrast at the diffraction points. Therefore, we determined that by analyzing diffraction data, it was possible to infer likely sediment variations that largely control permeability within fault zones.

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Section: Discussionmentioning

confidence: 99%

Diffraction imaging of polygonal faults within a submarine volcanic terrain, Maverick Basin, south Texas

2015

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“…decreasing ellipticity, with increasing fracture tilt. The parameters defining the interface are Vp=4.0 km/s Vs=2.7 km/s, g=2 g/cm 3 for the overlying isotropic halfspace and Vp=5.5 km/s, vs=2.9 km/s, g=2.9 g/cm 3 , sN=0.03, sT=0.18 for the anisotropic halfspace. The sN and sT parameters are dimensionless measures of the normal and tangential excess compliances introduced into a background isotropic medium by the addition of fractures.…”

Section: Discussionmentioning

confidence: 99%

Fracture Characterization Using Multicomponent Surface Seismic Data

Kristiansen¹,

Gaiser²,

Probert³

2005

All Days

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TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractIn reservoirs producing primarily from secondary porosity like fractures, the flow is largely controlled by the fracture system and characterizing these fractures is key to effectively managing these reservoirs. Aligned fractures will affect the average stiffness of the rocks even when fractures are smaller than seismic wavelengths. Small scale aligned fractures lead to variations in the seismic velocities that are directionally dependent, an effect known as anisotropy. Measuring this seismic anisotropy provides information on the fracture systems properties, such as fracture density and orientation. Such information can be used to identify sweet spots and in general be used for better reservoir management, like guiding directional and infill drilling. Since fractures are often nearly vertical to bedding the dominant seismic effect is azimuthal anisotropy, which is observed both on P-and S-waves. AVOA (azimuthal AVOeffect ) and variations in the NMO velocities have been used to estimate P-wave anisotropy. S-waves will split into one fast and one slow mode and this splitting is very sensitive to small changes in the subsurface. The fast shear-wave direction aligns with the fracture strike and the amount of time splitting between the fast and slow mode depends on fracture density. Apart from the difference in sensitivity between the P-and Swave measurements there are attributes of the fracture system that can only be observed on the S-wave data. The asymmetry in the converted waves (PS-data) can say something about the tilt of the fractures. Multicomponent seismic provides access to both the P-and S-wave azimuthal information. Combining these two can enable the extraction of information about the fluid in the fractures. In this paper we will give an overview of the theory and several cases where multi-component data has been used to characterize fractures and fracture attributes.

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“…The time difference between the fast and slow Swaves is affected by the propagation distance and direction as well as the degree of anisotropy (Li and Mueller, 1997). Because fracture density is mainly responsible for the degree of anisotropy, the time delay can be used to estimate fracture density (Lewis et al, 1991).…”

Section: S-wave Birefringencementioning

confidence: 99%

Advanced seismic processing/imaging techniques and their potential for geothermal exploration

et al. 2016

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International audienceSeismic reflection imaging is a geophysical method that provides greater resolution at depth than other methods and is, therefore, the method of choice for hydrocarbon-reservoir exploration. However, seismic imaging has only sparingly been used to explore and monitor geothermal reservoirs. Yet, detailed images of reservoirs are an essential prerequisite to assess the feasibility of geothermal projects and to reduce the risk associated with expensive drilling programs. The vast experience of hydrocarbon seismic imaging has much to offer in illuminating the route toward improved seismic exploration of geothermal reservoirs - but adaptations to the geothermal problem are required. Specialized seismic acquisition and processing techniques with significant potential for the geothermal case are the use of 3D arrays and multicomponent sensors, coupled with sophisticated processing, including seismic attribute analysis, polarization filtering/migration, converted-wave processing, and the analysis of the diffracted wavefield. Furthermore, full-waveform inversion and S-wave splitting investigations potentially provide quantitative estimates of elastic parameters, from which it may be possible to infer critical geothermal properties, such as porosity and temperature

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14. Case Studies of Multicomponent Seismic Data for Fracture Characterization: Austin Chalk Examples

Cited by 14 publications

References 41 publications

Diffraction imaging of polygonal faults within a submarine volcanic terrain, Maverick Basin, south Texas

Diffraction imaging of polygonal faults within a submarine volcanic terrain, Maverick Basin, south Texas

Fracture Characterization Using Multicomponent Surface Seismic Data

Advanced seismic processing/imaging techniques and their potential for geothermal exploration

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