Application of Geostatistical Modelling to Study the Exploration Adequacy of Uniaxial Compressive Strength of Intact Rock alongthe Behesht-Abad Tunnel Route

Document Type : Research Paper

Authors

1 School of Mining, College of Engineering, University of Tehran, Iran

2 School of Mining, College of Engineering, University of Tehran, Iran; Simulation and Data Processing Laboratory, School of Mining Engineering, University College of Engineering, University of Tehran, Iran

Abstract

Uniaxial compressive strength (UCS) is one of the most significant factors on the stability of underground excavation projects. Most of the time, this factor can be obtained by exploratory boreholes evaluation. Due to the large distance between exploratory boreholes in the majority of geotechnical projects, the application of geostatistical methods has increased as an estimator of rock mass properties. The present paper ties the estimation of UCS values of intact rock to the distance between boreholes of the Behesht-Abad tunnel in central Iran, using SGEMS geostatistical program. Variography showed that UCS estimation of intact rock using geostatistical methods is reasonable. The model establishment and validation was done after assessment that the model was trustworthy. Cross validation proved the high accuracy (98%) and reliability of the model to estimate uniaxial compressive strength. The UCS values were then estimated along the tunnel axis. Moreover, using geostatistical estimation led to better identification of the pros and cons of geotechnical explorations in each location of tunnel route.

Keywords


[1] Ellefmo, S. L. and Eidsvik, J. (2009). Local and spatial joint frequency uncertainty and its application to rock mass characterisation. Rock mechanics and rock engineering, 42.4: 667-688.
[2] Ruffolo, R. M. and Shakoor, A. (2009). Variability of unconfined compressive strength in relation to number of test samples. Engineering Geology, 108.1: 16-23.
[3] Ozbek, A., Unsal, M. and Dikec A. (2013). Estimating uniaxial compressive strength of rocks using genetic expression programming. Journal of Rock Mechanics and Geotechnical Engineering.
[4] Yilmaz, I. (2009). A new testing method for indirect determination of the unconfined compressive strength of rocks. International Journal of Rock Mechanics and Mining Sciences, 46.8: 1349-1357.
[5] Manouchehrian, A., Sharifzadeh, M. and Hamidzadeh Moghadam, R. (2012). Application of artificial neural networks and multivariate statistics to estimate UCS using textural characteristics. International Journal of 
Mining Science and Technology, 22.2: 229-236.
[6] Coates, D.F., and Parsons, R.C. (1966). Experimental criteria for classification of rock substances. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, Vol. 3. No. 3. Pergamon.
[7] Mark, C., McWilliams, L., Pappas, D., and Rusnak, J. (2004). Spatial trends in rock strength: can they be determined from coreholes. Proceedings of the 23rd International Conference on Ground Control in Mining. Morgantown, WV: West Virginia University, pp. 177B182.
[8] Ozturk, C.A., and Simdi, E. (2014). Geostatistical investigation of geotechnical and constructional properties in Kadikoy–Kartal subway, Turkey. Tunnelling and Underground Space Technology 41: 35-45.
[9] Hoerger, S.F. and Young, D.S. (1987). Predicting local rock mass behavior using geostatistics. The 28th US Symposium on Rock Mechanics (USRMS).
[10] Stavropoulou, M., Exadaktylos, G. and Saratsis, G. (2007). A combined three-dimensional geological-geostatistical-numerical model of underground excavations in rock. Rock mechanics and rock engineering 40.3: 213-243.
[11] Oh, S. (2013). Geostatistical integration of seismic velocity and resistivity data for probabilistic evaluation of rock quality.
Environmental Earth Sciences: 69:939–945.
[12] Öztürk, C. A. and Nasuf, E. (2002). Geostatistical assessment of rock zones for tunneling. Tunnelling and underground space technology, 17.3: 275-285.
[13] Ayalew, L., Reik, G. and Busch, W. (2002). Characterizing weathered rock masses— a geostatistical approach. International Journal of Rock Mechanics and Mining Sciences 39.1: 105-114.
[14] Gringarten, E. and Deutsch, V.C. (2001). Teacher's aide variogram interpretation and modeling. Mathematical Geology 33.4: 507-534.
[15] Journel, A.G. (1988). Fundamentals of geostatistics in five lessons. Stanford Center for Reservoir Forecasting, Applied Earth Sciences Department.
[16] Rajashekhar, M.R., Ellingwood, B.R. (1993). A new look at the response surface approach for reliability analysis. Structural safety, 12.3: 205-220.
[17] Sacks, J., Welch, W.J., Mitchell, T.J., and Wynn, H.P. (1989). Design and analysis of computer experiments. Statistical science, 4.4: 409-423.
[18] Hashemi, M. (2008). Rock mechanic’s reports, water supply project of the Central Plateau, Zayandehab Consulting, printed in Farsi.
[19] Armstrong, M. (1998). Basic Linear Geostatistics. Springer Verlag, Berlin, 155 pp.