LAUSR

The presence of fractures in a reservoir can have a significant impact on its effective mechanical and hydraulic properties. Many researchers have explored the seismic response of fluid-saturated porous rocks containing aligned planar fractures through the use of analytical models. However, these approaches are limited to the extreme cases of regular and uniform random distributions of fractures. The purpose of this work is to consider more realistic distributions of fractures and to analyze whether and how the frequency-dependent anisotropic seismic properties of the medium can provide information on the characteristics of the fracture network. Particular focus is given to fracture clustering effects resulting from commonly observed fracture distributions. To do so, we have developed a novel hybrid methodology combining the advantages of 1D numerical oscillatory tests, which allows us to consider arbitrary distributions of fractures, and an analytical solution that permits extending these results to account for the effective anisotropy of the medium. A corresponding numerical analysis indicates that the presence of clusters of fractures produces an additional attenuation and velocity dispersion regime compared with that predicted by analytical models. The reason for this is that a fracture cluster behaves as an effective layer and the contrast with respect to the unfractured background produces an additional fluid pressure diffusion length scale. The characteristic frequency of these effects depends on the size and spacing between clusters, the latter being much larger than the typical spacing between individual fractures. Moreover, we find that the effects of fracture clustering are more pronounced in attenuation anisotropy than velocity anisotropy data. Our results indicate that fracture clustering effects on fluid pressure diffusion can be described by two-layer models. This, in turn, provides the basis for extending current analytical models to account for these effects in inversion schemes designed to characterize fractured reservoirs from seismic data.