Sunday, May 12, 2019

AVO in VSPs

When a wavefront hits a boundary at vertical incidence, the amount of compressional energy reflected and transmitted is dependent only on the contrast of acoustic impedance- density times compressional velocity- of the rocks at that boundary. But when the incident angle is not 0 degree, the amount of compressional energy reflected of tranmitted depends on the angle of incidence, or source offset, and contrast in densities and shear and compressional velocities. In such cases, the reflection AVo can be measured and analyzed to yield information about lithology and pore fluid through their effects on density and compressional and shear velocities. 

Carrying out a walkaway VSP with the receivers straddling such a boundary allows direct measurement of the variation in amplitude with offset that arises from lithology and fluid properties above and below the reflector. The results can be analyzed for fluid and lithology identification in a wide zone around the well. Formation properties inferred from VSPs can be integrated with those interpreted from well logs and measured directly from cores. In this way the VSP can also provide independent calibration of the same amplitude variation seen across a surface seismic reflection point gather- a gather is thee collection of traces that reflect at the same point, but at different angles, or offsets.

Calibrating the surface seismic AVO data with the VSP AVO response brings added value by:


  • establishing viability of using AVO to map a reservoir.
  • reducing the risk involved with the added cost of AVO studies
  • improving the reliability of AVO interpretations
  • quantitatively assessing the effects of processing on the AVO response.


To establish whether AVO is applicable as an interpretation tool for a particular reservoir, the expected AVO response is usually modeled. This requires knowledge of the model parameters, including shear velocity. Dipole shear sonic logging tools are used to measure shear velocities even where this velocity is slower than the borehole fluid velocity.









However, use of density and velocity log data to model anticipated AVO anomalies has not always succeeded in fully explaining the AVO response observed on surface seismic gathers. The reasons for this are many and include reflectivity mismatches between surface seismic and log data, wave propagation effects through fine layers, tuning effects (constructive and destructive interference at seismic wavelengths), geometric effects, processing-related issues and intrinsic anisotropy.

Borehole seismic data can quantify these effects. VSPs provide an independent measure of the seismic AVO response and the ability to include necessary effects in the forward modeling to satifactorily explain the origins of the surface seismic AVO response. Anisotropy is one such effect - one that can both mimic and mask AVO responses, giving false hope for or concealing the presence of hydrocarbons. 

Informaiton about anisotropic velocities for forward modeling often comes from measurements made on cores. But being scale-dependent, anisotropy may be different at the seismic wavelength scale. Therefore, it is better to measure  the elastic anisotropy at the seismic scale. 

In 1994, at Schlumberger Cambridge Research in Cambridge, England, Doug Miller proposed a method to do this using the arrival times from a walkaway survey to provide a measure of compressional velocity anisotropy in a shale, and from this to characterize the elastic properties of that shale, governing compressional and vertically polarized shear waves.

Shale consists of finely- layered clay platelets and exhibits an anisotropy called transverse isotropy (TI). The acoustic properties vary depending on whether waves propagate with particle motions parallel or perpendicular to the platelet layers- often thought of as horizontally or vertically because the clays usually lie flat.

Miller proposed that the vertical slowness - the inverse of velocity - of a shale may be measured across an array of geophones for each shot point offset along a walkaway profile. And the horizontal slowness can be measured at a single receiver location for adjacent shots in the same profile, providing the subsurface layers are essentially flat. A crossplot of these measurements for each shot position defines the compressional anisotropic response of the shale. A curve fitted to these data points provides a solution to the equations that deliver shear anisotropy through a complete description of the elastic properties of the shale.

These research efforts have been put to practical use in the BP-operated Forties field in the UK sector of the North Sea. The ultimate aim is to enable AVO attributes to be mapped with confidence from 3D surface seismic data. To achieve this,  a detailed evaluation of shear velocity anisotropy in the formations overlying the Forties sand has been undertaken to build a velocity model. The data used included acoustic measurements from preserved shale and sand cores, a full suite of logs- including standard density and DSI Dipole Shear Sonic Imager Logs- in addition to walkaway, rig source and vertical-incidence VSP data.

Initially, two models were generated, one assuming the shale overlying the reservoir sand was isotropic and another in which TI anisotropy was introduced. Differences in amplitude response between the two models were immediately observed, particulary at far offsets for the interface between the shale and the reservoir sand at 1.07 normal incidence time. 

The predicted response assuming an anisotropic shale was validated by the amplitude measured in the calibration walkaway. This implies that the effect of the anisotropic velocity in the shale must be taken into account before attributing the AVO response in the surface seismic data to effects of fluid in the reservoir. 

It is clear from this study that the combination of AVO measurement from VSP and log-based, anisotropic forward modeling provides a powerful methodology for calibrating AVO responses observed on surface seismic data near wells in low dip structures. Where AVO analysis is used as the basis for hydrocarbon indication in fields with existing wells, the method helps identify the origin of observed AVO effects, determining whether large-scale AVO analysis and reprocessing effort are worthwhile in terms of achieving the desired objectives. 

The greater understanding of observed AVO effects should minimize the risk of missing genuine hydrocarbon-related AVO anomalies or of misinterpreting anomalies caused by other factors, such as anisotropy.

 
 






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