Mark P. Grasmueck, RSMAS University of Miami
mgrasmueck@rsmas.miami.edu
Alan G. Green,ETH Swiss Federal Inst. of Technology, Zürich
alan@aug.ig.erdw.ethz.ch

Abstract

Accurate prediction of fluid flow within fractured bedrock depends on a detailed understanding of the fracture network. Information from outcrops and boreholes must be augmented by geophysical data. Examples of state of the art geophysical methods show the possibilities and the limitations of characterizing fractured rock.

Seismic traveltime tomography, taking into account velocity anisotropy of the host rock, can be sensitive enough to show the extent of a hydraulically conductive zone and its response to changing fluid pressure between two wells spaced 100 meters apart. The resolution of the tomographic image however does not allow the identification of individual fractures and their geometries. An increase in resolution can be achieved by using the whole seismic wave trains for the tomographic inversion instead of first break picks only. Comparing the velocity distribution from the wavefield tomographic inversion with smoothed sonic logs provides a good match, as long as the wells are close to the 2-D tomographic plane. It remains difficult to correlate fractures between boreholes.

A 3-D ground-penetrating radar survey produced a high resolution image of the fracture network in a quarry in Switzerland to a depth of 30 meters. However at other sites, depth penetration of ground-penetrating radar is limited by clay content and saline pore water and can range from 0 to 50 meters for surface surveys.

Commercial applications show that automated data acquisition and processing of high-density 3-D geophysical surveys are practical. In order to get a better understanding of fractures and fluid flow within bedrock, all the subsurface data should be integrated into one shared and consistent digital model by a multidisciplinary team.

References

Albert, W., Bühnemann, J., Holliger, K., Maurer, H.R., Pratt, G., and Stekl, I., 1999, Grimsel Test Site, Further Development of Seismic Tomography: Nagra Tech. Rep. 97-05, 123p.

Grasmueck, M., 1996, 3-D ground-penetrating radar applied to fracture imaging in gneiss: Geophysics, 61,no. 4, 1050-1064.

Grasmueck, M., and Green, A.G., 1996, 3-D georadar mapping: Looking into the subsurface: Environmental & Engineering Geoscience, vol.II, no.2, 195-200.

Kneib, G., Kassel, A., and Lorentz, K., 2000, Automatic seismic prediction ahead of the tunnel boring machine: First Break, 18, no.7, 295-302.

Lehmann, F. and Green, A.G., 1999, Semiautomated georadar data acquisition in three dimensions: Geophysics, 64, no.3, 719-731.

Maurer, H.R., and Green, A.G., 1997, Potential coordinate mislocations in crosshole tomography: Results from the Grimsel test site, Switzerland: Geophysics, 62, no.6 1696-1709.

Vécsey, G., Holliger, K., Pratt, R.G., Dyer, B.C., and Green, A.G., 1998, Anisotropic seismic tomography of a potential hot dry rock reservoir before and during induced pressurization: Geophysical Research Letters, 25, no.11, 1991-1994.