We applied interpreted fracture data from borehole images towards modeling of azimuthal walkaround VSP attributes. The methodology is tested with a case study on data coming from a tight-gas field. Natural fractures inside a window of height h and located at depth d are included in an excess compliance model to obtain the formation anisotropic stiffness tensor. Five tensors are generated to model fast shear wave velocity as a function of VSP source azimuth. In addition, best approximative transverse-isotropy tensors are derived and applied in combination with a simple relation describing general walkaround attribute behavior. It is shown that with this approach, borehole images can be applied successfully to predict the walkaround VSP TR-ratio dependency on source azimuth. Good agreement between model and observation is achieved for a volume corresponding to the last two VSP shear wavelengths.
Walkaround VSP is a seismic data acquisition type whereby multiple sources at the surface are arranged azimuthally around a fixed receiver position in the well, keeping the source-receiver distance approximately constant. As discussed previously by Horne (2003), walkaround VSP can be a powerful tool in establishing anisotropy directions when the anisotropy is caused by vertical or semi-vertical fractures and fracture systems. In this way, seismic attributes such as the Transverse over Radial (TR) displacement ratio can be applied to deduce information on the dominant fracture orientation in the volume probed by the VSP survey.
In this case study, we discuss a well in which walkaround VSP was acquired in addition to borehole images and sonic. This abstract focuses on the combination of VSP and borehole images, while the application of borehole images towards modeling of borehole sonic response is the topic of the companion abstract by the same authors (Prioul et al. (2008)). The aim of the study is to try and see to what extent information at the borehole wall (images) can be used to predict or explain seismic behavior at a much larger scale. We will first briefly discuss the data available (processed VSP and geological features from borehole images), and then proceed with the methodology applied to turn borehole resistivity images into results that can be compared, at least qualitatively, with VSP azimuthal attributes. Figure 1 gives a schematic overview of the VSP survey dimensions and the logged interval (borehole images and sonic). The vertical well is drilled in a tight-gas sand environment in North-Africa. Though the depth axes in Figure 1 are scaled by some factor (fact); for confidentiality reasons, all dimensions are shown in the correct relative proportions.
The seismic data obtained in the VSP survey were processed to obtain the shear radial and transverse displacement components per source azimuthal location. The radial displacement is the horizontal wavefield displacement component aligned towards the source. The horizontal transverse displacement is orthogonal to the radial direction. The ratio of transverse over radial displacement, from hereon simply referred to as the TRratio, is a useful attribute as it can be shown to be minimum when the source-receiver line is either perpendicular or parallel to the fracture system.
We estimate fracture elastic compliances using a combination of image and sonic logs from a typical borehole survey in a naturally fractured reservoir. Borehole dipole sonic anisotropy related to the effect of drilling-induced (DI) and natural fracturesis modeled using a classical excess-compliance fracture model. We extract the orientation of individual fractures from borehole image log analysis. The analysis is focused on the log depth interval where fracture-induced anisotropy is observed, and where the maximum horizontal stress direction is not aligned with the strike of natural fractures. Fracture compliances are estimated in two steps by first selecting the fractures that honor the fast-shear azimuth, and second by using a grid search method minimizing the sonic slowness anisotropy difference. Two fracture compliance parameters are used, one per fracture type (natural and DI). We first model the effect of natural and DI fractures including all fractures observed on the images. Predicted fast-shear azimuths are shown to be slightly biased by the presence of non-compliant fractures in each fracture type. Next, we introduce a selection criteria based on the fast-shear azimuth to reject non-compliant fractures. Finally,we estimate fracture compliances using sonic slowness difference before and after the selection process and discuss the results.
The characterization of natural fractures in the subsurface is commonly done using multiple measurements such as borehole images, sonic anisotropy logs, borehole seismic and surface seismic anisotropy. Finding a consistent quantitative interpretation of the measurements is often challenging because of the different physics involved in addition to the different volumes of investigation. On one hand, borehole electrical or ultrasonic images provide high resolution quantification of fracture orientation and type, but the depth of investigation is limited to the borehole wall vicinity. On the other hand, sonic and seismic anisotropy measurements provide effective properties of the elastic medium in a volume related to their wavelength (i.e., meter-scale for sonic, tens of meters for borehole seismic, and hundreds of meters for surface seismic), but at the same time their interpretation is subject to ambiguity on the cause of anisotropy. Sonic and seismic measurements also typically do not provide properties of individual fractures, be it elastic properties or exact orientation.
The question of finding a joint quantitative model using geological fractures observed on borehole images to model and interpret fracture-induced dipole sonic anisotropy was recently addressed by Prioul et al. (2007) using a classical excess-compliance fracture model (Sayers and Kachanov (1995); Schoenberg and Sayers (1995)). It was shown that using just two fracture compliance parameters, one for natural fractures and one for drilling-induced (DI) fractures, was an excellent first-order approximation to explain the fracture-induced anisotropy response. However, the question of discriminating between compliant and non-compliant fractures within each fracture type (natural and DI) was not addressed. Indeed, selecting fractures that have a significant impact on the elastic medium is required for:
Accurate estimation of fracture compliances,
Improved understanding of the complex relationship between fractures and stress, and
Proper calibration of near-wellbore anisotropic models for seismic applications.