A fracture network model provides a wealth of information concerning the characteristics of a rock mass, including fracture intensity, block size, and connectivity. This paper identifies methods to utilize information derived from DFN models. The fracture intensity of a DFN can be analysed for individual or grouped subvolumes of the model. A DFN is discretized into volumetric elements (voxels). Stochastic DFN models measuring 25 × 25 × 25 m3 are modeled with identical attributes. Fractures are modeled as non-planar and non-persistent, and orientations varied to generate a variety of block shapes and sizes. The voxels used for metrics analysis range in size from 1 m3 to 1 953 m3, representing from 23 to 253 voxels. Fracture intensity is measured as a P32 value for all elements. The coefficient of variation (CV%) of fracture intensity is calculated for each voxelization to generate a curve characteristic of a particular DFN model. An estimate of the in situ block size distribution (IBSD) is made by considering the number of unfractured voxels (null blocks). The fracture intensity, CV% of fracture intensity and IBSD values derived from these DFNs can be used as input to a variety of secondary models.
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53rd U.S. Rock Mechanics/Geomechanics Symposium
June 23–26, 2019
New York City, New York
DFN Variability Analysis Through Voxelization
W. R. Junkin;
W. R. Junkin
MIRARCO Mining Innovation / Canada Laurentian University
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L. Fava
L. Fava
MIRARCO Mining Innovation
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Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, New York City, New York, June 2019.
Paper Number:
ARMA-2019-0345
Published:
June 23 2019
Citation
Junkin, W. R., Ben-Awuah, E., and L. Fava. "DFN Variability Analysis Through Voxelization." Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, New York City, New York, June 2019.
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