Skip to main content

Fault detection in 3D by sequential Gaussian simulation of Rock Quality Designation (RQD)

Case study: Gazestan phosphate ore deposit, Central Iran

Abstract

Gazestan phosphate ore deposit (Central Iran) is an apatite deposit which is instrumental in selecting the method of excavation. The position of fault systems and the condition of rock quality also play a role in the method used for mineral resources and ore reserves estimation. Conversely, the Rock Quality Designation (RQD) is a parameter that provides a quantitative judgment of rock mass quality obtained from drill cores. This factor can be applied to detect the fractured zones which occur due to fault systems. Additionally, the faulted areas can be determined by surface geological map and a few by core drilling. Some of the faulted areas are not distinguishable in the surface and are covered by soils, especially within 3D modeling and visualization. In this study, an attempt has been made to establish a relationship between the RQD percentages which were geostatistically simulated and faulted areas through the region. In comparison, the results showed that low RQD domains (RQD <20 %) can be interpreted as fault zones; high RQD domains (RQD >50 %) correspond to less fractured areas, and the contact between high and low RQD domain is gradual. Therefore, this categorization of RQD domains can be incorporated to detect the faulted zones in 3D models for mine design. Based on the categorization, the uncertainty within the area was calculated to introduce two new core drilling points for the completion of this phase of exploratory grid from the fault structural viewpoint, in order to have a proper model of ore reserve to estimate. It was concluded that this procedure can be utilized for conceptual comprehension of fault trends in 3D modeling for the method selection of excavation and complete the estimation procedure phase.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

References

  1. Asghari O, Madani N (2011) A new approach for the geological risk evaluation of coal resources through a geostatistical simulation. Arab J Geosci. doi:10.1007/s12517-011-0391-7

  2. Barton CC, Larsen E, Page WR, Howars TM (1988) Characterising fractured rock for fluid flow, geomechanical and paleostress modeling: methods and preliminary results from Yucca Mountain, Nevada (methods for parameterizing fracture characteristics at the scale of large outcrops). U.S. Geological Survey, Bulletin, March 3

  3. Basarir H, Kumral M, Karpuz C, Tutluoglu L (2010) Geostatistical modeling of spatial variability of SPT data for a borax stockpile site. Eng Geol 114:154–163

    Article  Google Scholar 

  4. Caine JS, Evans JP, Forster CB (1996) Fault zone architecture and permeability structure. Geology 24:1025–1028

    Article  Google Scholar 

  5. Chester FM, Logan JM (1986) Implications for mechanical properties of brittle faults from observations of the Punchbowl Fault zone, California. Pure Appl Geophys 124(1/2):79–106

    Article  Google Scholar 

  6. Chester FM, Logan JM (1987) Composite planar fabric of gouge from the Punchbowl Fault, California. J Struct Geol 9:621–634

    Article  Google Scholar 

  7. Chester FM, Evans JP, Biegel RL (1993) Internal structure and weakening mechanisms of the San Andreas fault. J Geophys Res 98:771–786

    Article  Google Scholar 

  8. Deere DU (1989) Rock quality designation (RQD) after 20 years. U.S. Army Corps Engrs Contract Report GL-89-1. Waterways Experimental Station, Vicksburg, MS

  9. Deere DU, Deere DW (1988) The rock quality designation (RQD) index in practice. In L. Kirkaldie (ed) Rock classification systems for engineering purposes. ASTM Special Publication 984, 91–101. Am. Soc. Test. Mater., Philadelphia

  10. Deere DU, Hendron AJ, Patton FD, Cording EJ (1967) Design of surface and near surface construction in rock. In: C. Fairhurst (ed) Failure and breakage of rock. Proc. 8th U.S. symp. rock mech, 237–302. Soc. Min. Engrs, Am. Inst. Min. Metall. Petroleum Engineers, New York

  11. Dowd PA (1993) Geostatistical simulation. Course notes for the MSc in Mineral Resource and Environmental Geostatistics, University of Leeds, 123 pp

  12. Egana M, Arancibia E, Villages F, Ortiz JM (2008) Geostatistics applied to geotechnical parameters. 3rd International Conference on Mining Innovation. Santiago, Chile, pp. 137–146

  13. Emery X (2008) Statistical tests for validating geostatistical simulation algorithms. Comput Geosci 34:1610–1620

    Article  Google Scholar 

  14. Escuder Viruetea J, Carbonellb R, Martı’b D, Pe’rez-Estau’nb A (2003) 3D stochastic modeling and simulation of fault zones in the Albalá granitic pluton, SW Iberian Variscan Massif. J Struct Geol 25:1487–1506

    Article  Google Scholar 

  15. Goddard J, Evans JP (1995) Chemical changes and fluid–rock interaction in faults of crystalline thrust sheets, northwestern Wyoming, USA. J Struct Geol 17:533–547

    Article  Google Scholar 

  16. Goovaerts P (1999) Impact of simulation algorithm, magnitude of ergodic fluctuations and number of realization on the spaces of uncertainty flow properties. Stoch Env Res Risk A 13:161–182

    Article  Google Scholar 

  17. Hassanipak AA, Sharafodin M (2003) GET: a function for preferential site selection of additional borehole drilling. Explor Min Geol 13:139–146

    Article  Google Scholar 

  18. Jamali, Sepehri (2008) Gazestan ore deposit exploration. Geological survey of Iran. Report No. 324. 180 pp

  19. Journel AG (1989) Fundamentals of geostatistics in five lessons. American Geophysical Union Publication, Washington, DC, p 40

    Book  Google Scholar 

  20. Li S, Dimitrakopoulos R, Scott J, Dunn D (2008) Quantification of geological uncertainty and risk using stochastic simulation and applications in the coal mining industry. Ore Body Model Strateg Mine Plan Spectr Ser 14:253–260

    Google Scholar 

  21. Merritt AH (1972) Geologic prediction for underground excavations. In KS Lane and LA (eds) Garfield Proc. North American rapid excav. tunneling Conference, Chicago, 1, 115–132. Soc. Min. Engrs, Am. Inst. Min. Metall. Petroleum Engineers, New York

  22. Remy NN, Wu J, Boucher A (2008) Applied geostatistics with SGeMS: A user guide. Cambridge University Press, Cambridge, p 264

    Google Scholar 

  23. Scholz CH, Anders MH (1994) The permeability of faults. In: the mechanical involvement of fluids in faulting. US Geolog Surv Open-File Rep 94–228:247–253

    Google Scholar 

  24. Schulz SE, Evans JP (1998) Spatial variability in microscopic deformation and compositions of the Punchbowl fault, southern California: implications for mechanisms, fluid–rock interaction, and fault morphology. Tectonophysics 295:223–244

    Article  Google Scholar 

  25. Schulz SE, Evans JP (2000) Mesoscopic structure of the Punchbowl Fault, Southern California and the geologic and geophysical structure of active strike–slip faults. J Struct Geol 22:913–930

    Article  Google Scholar 

  26. Sen Z (2009) Spatial modeling principles in earth sciences. Springer-Verlag, New York

    Book  Google Scholar 

  27. Soltani S, Hezarkhani A (2011) Proposed algorithm for optimization of directional additional exploratory drill holes and computer coding. Arab J Geosci. doi:10.1007/s12517-011-0323-6

  28. Verly G (1986) Multigaussian kriging — a complete case study, 19. APCOM Symposium Proceedings. Society of Mining Engineers, Littleton, CO, pp. 283–298

  29. Villaescusa E, Potvin Y (2004) Ground support in mining and underground construction. Taylor and Francis, London

    Google Scholar 

  30. Yu Y (2010) Geostatistical interpolation and simulation of RQD measurement. MSc thesis in Mining Engineering, University of British Columbia, 90 pp

Download references

Acknowledgement

The authors acknowledge the financial support of the University of Tehran for this research under grant number 28350/1/04.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Nasser Madani Esfahani.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Madani Esfahani, N., Asghari, O. Fault detection in 3D by sequential Gaussian simulation of Rock Quality Designation (RQD). Arab J Geosci 6, 3737–3747 (2013). https://doi.org/10.1007/s12517-012-0633-3

Download citation

Keywords

  • RQD
  • Sequential Gaussian simulation
  • Gazestan ore deposit. 3D fault detection