Joint network modelling with a validation exercise in Stripa mine, Sweden

Abstract In this paper, eight joint geometry modelling schemes are suggested and applied to a set of Stripa mine joint data to build 3-D joint networks to a granitic rock mass. These modelling schemes include investigations for statistical homogeneity of the rock mass, corrections for sampling biases, and applications of stereological principles, to estimate 3-D joint geometry parameters from 1-D or 2-D joint geometry parameter values. Results show the possibility of obtaining different estimates for both joint size and joint intensity parameters through these different schemes. This indicates the importance of performing validation studies for developed joint geometry modelling schemes. Validation procedures developed and performed indicated the need to try out different schemes in modelling joint geometry parameters in order to establish realistic 3-D joint geometry modelling schemes which provide good agreement with field data during verification. It is important to realize that different types of joint geometry modelling schemes are needed to model joint networks in different types of rock formations.

[1]  G. W. Wathugala,et al.  A general procedure to correct sampling bias on joint orientation using a vector approach , 1990 .

[2]  S. Priest,et al.  ESTIMATION OF DISCONTINUITY SPACING AND TRACE LENGTH USING SCANLINE SURVEYS , 1981 .

[3]  Pinnaduwa Kulatilake,et al.  The density of discontinuity traces in sampling windows , 1984 .

[4]  Herbert H. Einstein,et al.  Characterizing rock joint geometry with joint system models , 1988 .

[5]  C. M. Barton.  Analysis Of Joint Traces , 1978 .

[6]  Masanobu Oda,et al.  FABRIC TENSOR FOR DISCONTINUOUS GEOLOGICAL MATERIALS , 1982 .

[7]  Z. Sen,et al.  Discontinuity spacing and RQD estimates from finite length scanlines , 1984 .

[8]  Kevin Hestir,et al.  Some Geostatistical Tools For Incorporating Spatial Structure In Fracture Network Modeling , 1987 .

[9]  Richard E. Goodman,et al.  Determination of principal joint frequencies , 1985 .

[10]  R. J. Shanley,et al.  Delineation and analysis of clusters in orientation data , 1976 .

[11]  P. M. Warburton,et al.  A STEREOLOGICAL INTERPRETATION OF JOINT TRACE DATA , 1980 .

[12]  Stanley M. Miller.  A statistical method to evaluate homogeneity of structural populations , 1983 .

[13]  Pinnaduwa Kulatilake,et al.  Probabilistic modelling of joint orientation , 1990 .

[14]  Pinnaduwa Kulatilake,et al.  RELATION BETWEEN DISCONTINUITY SIZE AND TRACE LENGTH. , 1986 .

[15]  D. M. Cruden.  Describing the size of discontinuities , 1977 .

[16]  Kevin Hestir,et al.  Three-dimensional statistical modelling of a fractured rock mass—an example from the Fanay-Augères mine , 1989 .

[17]  Pinnaduwa Kulatilake,et al.  Estimation of mean trace length of discontinuities , 1984 .

[18]  Pinnaduwa H.S.W. Kulatilake,et al.  Analysis of structural homogeneity of rock masses , 1990 .

[19]  Björn Dverstorp,et al.  Conditional simulations of fluid flow in three-dimensional networks of discrete fractures , 1987 .

[20]  Mc Bridges.  Presentation of Fracture Data for Rock Mechanics , 1975 .

[21]  D. Stoyan,et al.  Stochastic Geometry and Its Applications , 1989 .

[22]  D. Heliot.  Generating a blocky rock mass , 1988 .

[23]  G. Marsily,et al.  Modeling fracture flow with a stochastic discrete fracture network: calibration and validation: 1. The flow model , 1990 .

[24]  Gregory B. Baecher,et al.  Trace Length Biases In Joint Surveys , 1978 .

[25]  K. J. Arnold.  On spherical probability distributions , 1941 .

[26]  Nicholas Anthony Lanney,et al.  Statistical description of rock properties and sampling. , 1978 .

[27]  Mahtab,et al.  Similarity Test For Grouping Orientation Data In Rock Mechanics , 1984 .

[28]  Lawrence L. Kupper,et al.  Probability, statistics, and decision for civil engineers , 1970 .