1887

Abstract

Summary

The rock quality designation (RQD) is an important factor for geotechnical work in mining operations. RQD is defined by rock core measurement, which is subjective and time consuming procedure. It would be more effective if we could indirectly define RQD from well logs. We show using engineering and geophysical borehole data from the Kevitsa Mine how we may develop relationships between Vp and RQD. For the prediction to be robust the data needs to be clustered, which for the Kevitsa data four clusters were necessary and sufficient. Our predicted RQD using clustered characteristics shows a very good match with the RQD values from core measurements. This encouraging result that demonstrates how low cost, routine, borehole data can greatly improve the understanding of subsurface engineering properties of a prospect. Furthermore, adding surface or borehole tomography data would create volumetric data that can guide engineering decisions about design and better risk management strategies.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201802592
2018-09-09
2024-03-28
Loading full text...

Full text loading...

References

  1. Barton, N.
    [2006] Rock Quality, Seismic Velocity, Attenuation and Anisotropy, CRC Press, ISBN 9780415394413.
    [Google Scholar]
  2. Bery, A., A., and Saad, R.
    [2012] Correlation of Seismic P-Wave Velocities with Engineering Parameters (N Value and Rock Quality) for Tropical Environmental Study, International Journal of Geosciences, 3, 749–757. http://dx.doi.org/10.4236/ijg.2012.34075
    [Google Scholar]
  3. Deere, D. U. and Deere, D. W.
    [1988] The Rock Quality Desig-nation (RQD) Index in Practice, In: L.Kirkaldie, Ed., Rock Classification System for Engineering Purposes, ASTM STP 984, American Society for Testing and Materials, Philadelphia, pp. 91–101. doi: 10.1520/STP48465S
    https://doi.org/10.1520/STP48465S [Google Scholar]
  4. Kieu, D. T., and Kepic, A.
    , [2018] Building 3D Model of Rock Quality Designation Assisted by Co-Operative Inversion of Seismic and Borehole Data: ASEG Extended Abstracts, v. 2018, no. 1, p. 1–5.
    [Google Scholar]
  5. Malehmir, A. Juhlin, C., Wijns, C., Urosevic, M., Valasti, P., and Koivisto, E.
    , [2012] 3D reflection seismic imaging for open-pit mine planning and deep exploration in the Kevitsa Ni-Cu-PGE deposit, northern Finland. Geophysics, 77(5), WC95–WC108. https://doi.org/10.1190/geo2011-0468.1
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201802592
Loading
/content/papers/10.3997/2214-4609.201802592
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error