Skip to main content
SpringerLink
Log in

Improving Reliability of Structural Domaining for Engineering Projects

  • Original Paper
  • Published:
Rock Mechanics and Rock Engineering Aims and scope Submit manuscript

Abstract

Despite major improvements over the past several decades in computer methods for analyzing and synthesizing exploration and site investigation geological data for engineering purposes, which should have decreased project risk, unexpected failures and construction problems still occur. Often, this unexpectedness can be tied back to inadequate structural geological understanding of actual site-specific conditions. Part of this diminished appreciation of structural geological controls on rockmass behaviour can likely be attributed to inappropriate use of computational geostatistics, block modelling and geomechanics computer codes, without significant structural geological input. Part may be because of inadequate domaining in the raw data analysis phase, such that no differentiation was ever made between uncertainties due to true natural variability versus those due to data inadequacy. Modelled data error issues cannot easily be resolved once mixing and smearing of parameters have occurred as a result of earlier inappropriate synthesis of an uncontrolled database. The increased use, industry-wide, of inadequately calibrated, often totally unverified, geomechanics computer modelling for design of civil or mining projects is a worrying trend that needs reversing. Much more attention needs to be paid to properly sub-dividing project sites into realistic geological entities through use of rigorous geological structural domaining techniques, such that much better understanding is gained of project-specific geological risk. This in turn will lead to improved reliability and representativeness in project geomechanical parameter selection for use in design. This paper attempts to set out some guidelines to help practitioners undertake more rigorous domaining, as an aid to parameter selection for design.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Notes

  1. GSI = Geological Strength Index (Marinos and Hoek 2000).

    RMR = Rock Mass Rating (Bieniawski 1973).

    Q = Rock Quality (Barton et al. 1974).

  2. mi = Hoek-Brown intact frictional parameter; UCSi = Intact Unconfined Compressive Strength; Ei = Intact Modulus.

    JRC, Jr, Ja = Joint parameters of Q-system; JCond = Joint parameter of RMR system.

  3. RQD = Rock Quality Designation

    TCR = Total Core Recovery (%)

    SCR = Solid (cylindrical) Core Recovery (%)

References

  • Baecher GB (1983) Statistical analysis of rock mass fracturing. Math Geol 15:329–348

    Article  Google Scholar 

  • Barnett WP, Carter TG (2020) Structural domaining for engineering projects. In: Proceedings of the 54th US rock mechanics/geomechanics symposium, Golden, Colorado, ARMA Paper 20–2105, 12 pp

  • Barton N, Lien R, Lunde J (1974) Engineering classification of rock masses for the design of tunnel support. Rock Mech 6:189–236

    Article  Google Scholar 

  • Ben-Zion Y, Sammis C (2003) Characterization of fault zones. Pure Appl Geophys 160:677–715

    Article  Google Scholar 

  • Bianchi G, Perello P, Venturini G, Dematteis A (2009) Determination of reliability in geological forecasting for tunnel projects: the method of R-Index and its application on two case studies. IAEG Ital 2009:1–18

    Google Scholar 

  • Bieniawski ZT (1973) Engineering classification of jointed rock masses. Transactions. S Afr Instit Civ Eng 15(12):335–344

    Google Scholar 

  • Bieniawski ZT (1976) Rock mass classification in rock engineering. In: Proceedings of the Symposium on Exploration for Rock Engineering, Johannesburg, pp 97–106

  • Bieniawski ZT (1989) Engineering rock mass classifications. In: A complete manual for engineers and geologists in mining, civil, and petroleum engineering. John Wiley and Sons, New York, 272 pp

  • Bistacchi A, Massironi M, Menegon L (2010) Three-dimensional characterization of a crustal-scale fault zone: the Pusteria and Sprechenstein fault system (Eastern Alps). J Struct Geol 32:2022–2041

    Article  Google Scholar 

  • Bond CE, Shipton ZK, Gibbs AD, Jones S (2008) Structural models: optimizing risk analysis by understanding conceptual uncertainty. First Break. https://doi.org/10.3997/1365-2397.2008006

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Carter TG (1992) Prediction and uncertainties in geological engineering and rock mass characterization assessments. In: Proceedings of the 4th Italian conf engineering rock mechanics, Torino, pp 1.1–1.22

  • Carter TG (2012) Geotechnical concerns for deep mountain drives. TunnelTalk, 12 May. https://www.tunneltalk.com/TunnelTech-May12-Himalayas-ground-conditions-challenge-innovation-for-successful-TBM-tunnelling.php

  • Carter TG (2015) On increasing reliance on numerical modelling and synthetic data in rock engineering. In: Proceedings 13th ISRM international congress on rock mechanics, Montreal, Canada, Paper 821, 17pp

  • Carter TG (2018) Suggested standards for improving structural geological definition for open pit slope design. In: Proceedings of slope stability 2018, international symposium on slope stability in open pit mining and civil engineering, XIV Congreso, Mineria-2018 (IERM), Sevilla, Paper #102, 26 pp

  • Carter TG (2021) Discussion on learning from difficult rock TBM drive experiences TunnelTalk, 28 January. https://www.tunneltalk.com/Discussion-Forum-Jan2021-Robbins-experience-of-long-distance-difficult-rock-TBM-drives.php

  • Carter TG, Marinos V (2020) Putting geological focus back into rock engineering design. Rock Mech Rock Eng 53(10):4487–4508

  • Carter TG, Barnett WP (2021) Quantifying reliability in geological prediction. TunnelTalk, 15 March, 4 pp. https://www.tunneltalk.com/TunnelTECH-Mar2021-Quantifying-reliability-in-geological-prediction.php

  • Carter TG, Carvalho JL (2020) Pitfalls in defining parameter, domain and boundary inputs for realistic rock mechanics modelling. 6th tv-seminar 30 September, uploaded Nov 2020. https://youtu.be/W1jpKV2J4x4

  • Carter TG, Marinos V (2014) Use of GSI for rock engineering design. In: Proceedings of first international conference on applied empirical design methods in mining, Lima-Perú, 9–11th June, 19 pp

  • Carter TG, Miller RI (1995) Crown pillar risk assessment—cost effective measures for mine closure remediation planning. Trans Inst Min Metl 104:A41–A57

    Google Scholar 

  • Carter TG, Otto SA, Carvalho JL, Popielak R, Vardiman D, Hladysz Z (2011) Preliminary design of the 4850-level excavations at DUSEL, Part 1—geological engineering evaluation of rock mass conditions. Paper ARMA 11–482. In: Proceedings of 45th US Rock Mechanics/Geomechanics Symposium, San Francisco

  • Carter TG, Rogers SF, Taylor JJL, Smith J  (2015)  Unravelling Structural Fabric — a necessity for Realistic Rock Mass Characterization for Deep Mine Design.  In: Proc. Conf. on Underground Design Methods. Potvin Y (ed.) Australian Centre for Geomechanics, Perth, ISBN 978-0-9924810-3-2.  p 10

  • Campbell R, Barnett WP, Levy M (2014)  A structural geology matrix for geotechnical design in hard rock. In: international symposium on slope stability in open pit mining and civil engineering, Cape Town, pp 475–484

  • CIM (2014) Updated Canadian Institute of Mining Definition Standards with respect to Canadian Securities Administrators (CSA) National Instrument 43–101. http://web.cim.org/standards

  • Clark I (1979) Practical geostatistics, vol 3. Applied Science Publishers, London

    Google Scholar 

  • Cowen EJ (2014) X-ray plunge projection. Understanding structural geology from grade data. AusIMM Monogr 30(2014):207-220.

    Google Scholar 

  • Cowen EJ (2017) The fundamental reason why your geological models may be wrong. http://www.orefind.com/blog/orefind_blog/2017/10/23/the-fundamental-reason-why-your-geological-models-may-be-completely-wrong

  • Dershowitz WS, Herda H (1992) Interpretation of fracture spacing and intensity. In: Proceedings of the 33rd US symposium on rock mechanics, Balkema, Rotterdam, pp 757–766

  • Emery X, Ortiz JM (2004) Shortcomings of multiple indicator kriging for assessing local distributions. Appl Earth Sci 113(4):249–259

    Article  Google Scholar 

  • Faulkner DR, Jackson CAL, Lunn RJ, Schlische RW, Shipton ZK, Wibberley CAJ, Withjack MO (2010) A review of recent developments concerning the structure, mechanics and fluid flow properties of fault zones. J Struct Geol 32(11):1557–1575

  • Fasching F, Vanek R (2013) Characterization and classification of fault zones. Workshop on “Characterization of Fault Zones”. Austrian Society for Geomechanics, Salzburg Congress, Austria, Extended Abstracts, pp 1–5

  • Fookes PG (1968) Contribution to discussion on the engineering of Mangla dam. In: Proceedings of Institute for Civil Engineers, vol 41, para 892–900, pp 119–120

  • Fookes PG (1997) Geology for engineers: the geological model, prediction and performance. Q J Eng Geol 30:293–424

    Article  Google Scholar 

  • Gillespie PA, Howard CB, Walsh JJ, Watterson J (1993) Measurement and characterization of spatial distributions of fractures. Tectonophysics 226:114–141

    Article  Google Scholar 

  • Gómez-Hernández JJ, Srivastava RM (1990) ISIM3D: an ANSI-C three-dimensional multiple indicator conditional simulation program. Comput Geosci 16(4):395–440

    Article  Google Scholar 

  • Guibal D (2001) Variography—a tool for the resource geologist. In: Edwards AC (ed) Mineral resource and ore reserve estimation—The AusIMM guide to good practice. The Australian Institute of Mining and Metallurgy, Melbourne

  • Hoek E (1994) The challenge of input data in rock engineering. ISRM News J 2(2):23–24

    Google Scholar 

  • Hoek E (2009a)  Conclusions Slide 40 of 40 from Keynote presentation on Recent Experiences in Tunnelling.  Athens, October. https://slideplayer.com/slide/3470431/12/images/39/CONCLUSIONS.jpg

  • Hoek E (2009b) Fundamentals of Slope Design  Keynote address at Slope Stability 2009, Santiago, Chile, 9-11 November 2009. 26pp.  https://www.rocscience.com/assets/resources/learning/hoek/2009-Fundamentals-of-Slope-Design.pdf

  • Hoek E, Hutchinson J, Kalenchuk K, Diederichs M (2009) Appendix 3: Influence of in situ stresses on open pit design. Guidelines for Open Pit Slope Design. CSIRO Publishing, Collingwood, Australia, pp 437–445

  • Hoek E, Carter TG, Diederichs MS (2013) Quantification of the geological strength index chart. In: Proceedings of 47th US rock mechanics symposium, San Francisco, Paper 13–672, 8 pp

  • Hudson JA, Feng XT (2007) Updated flowcharts for rock mechanics modelling and rock engineering design. Int J Rock Mech Min Sci 44(2):174–195

  • Itasca (2013) Flac3D, v.5—Software for fast Lagrangian analysis of continua in 3 dimensions. Itasca Consulting Group Inc, Minneapolis, MN, USA

  • JORC (2012) Australasian Code for reporting of exploration results, mineral resources and ore reserves. (The JORC Code) (The Joint Ore Reserves Committee of The Australasian Institute of Mining and Metallurgy, Australian Institute of Geoscientists and Minerals Council of Australia). http://www.jorc.org/docs/JORC_code_2012.pdf

  • Journel AG (1974) Geostatistics for conditional simulation of ore bodies. Econ Geol 69(5):673–687

    Article  Google Scholar 

  • Kim Y-S, Peacock DCP, Sanderson DJ (2004) Fault damage zones. J Struct Geol 26:503–517

    Article  Google Scholar 

  • Krueger JI, Funder DC (2004) Towards a balanced social psychology: Causes, consequences, and cures for the problem-seeking approach to social behavior and cognition. Behav Brain Sci 27(3):313–327

  • Marinos P, Hoek E (2000) GSI: A geologically friendly tool for rock-mass strength estimation. In: Proceedings of GeoEng2000 international conference on geotechnical and geological engineering, Melbourne, 19–24 Nov 2000, p 1422–1446

  • Martin MW, Tannant DD (2004) A technique for identifying structural domain boundaries at the EKATI Diamond Mine. Eng Geol 74:247–264

    Article  Google Scholar 

  • Passchier CW, Trouw RAJ (2005) Microtectonics, 2nd edn. Springer, Berlin, p 366

    Google Scholar 

  • Peck RB (1985) The last sixty years. In: Proceedings of 11th international conference on soil mechanics, San Francisco. Golden jubilee volume, pp 123–133; reproduced in NGI publication 207, (2000) Ralph B. Peck, Engineer, Educator. In: Elmo D, Kaare F (eds) A man of judgement, 76 pp

  • Perello P (2011) Estimate of the reliability in geological forecasts for tunnels: toward a structured approach. Rock Mech Rock Eng 44(6):671

    Article  Google Scholar 

  • Perello P (2015) Are reliable geological forecasts possible for long and deep tunnels? Experience gained from some big railway project in Italy. In: Third Arabian tunneling conference and exhibition, Dubai (UAE), pp 23–25

  • Perello P, Venturini G, Delle Piane L, Martinotti G (2003) Geostructural mapping applied to underground excavations: updated ideas after a century since the first trans-alpine tunnels. In: Proceedings of Rapid Excavation and Tunnelling Conference, New Orleans, p 581

  • Perello P, Venturini G, Dematteis A, Bianchi GW, Delle Piane L, Damiano A (2005) Determination of reliability in geological forecasts for linear underground structures: the method of the R-Index. In: Proceedings of Geoline 2005––Lyon (F), 23–25 May, p 8

  • Priest SD (1993) Discontinuity analysis for rock engineering. Chapman and Hall, New York, p 473

    Book  Google Scholar 

  • Savage N, Nicholas L, Wilson A, Seery J (2013) Visual communication of geological confidence – A move toward a less subjective approach. Iron Ore Conference, Perth, August 2013

  • Schlotfeldt P, Carter TG (2019) A new and unified approach to improved scalability and volumetric fracture intensity quantification for GSI and rockmass strength and deformability estimation. Int J Rock Mech Min Sci 110:48–67

    Article  Google Scholar 

  • Stead D, Wolter A (2015) A critical review of rock slope failure mechanisms: the importance of structural geology. J Struct Geol 74:1–23

    Article  Google Scholar 

  • Stegman CL (2001) How domain envelopes impact on the resource estimate—case studies from the Cobar Gold Field, NSW, Australia. In: Edwards AC (ed) Mineral resource and ore reserve estimation—the AusIMM guide to good practice. The Australian Institute of Mining and Metallurgy, Melbourne

    Google Scholar 

  • US National Committee on Tunnelling Technology (USNCTT) (1984) Commission on engineering and technical systems—geotechnical site investigations for underground projects  vol 1 overview of practise, legal issues, evaluation of cases, conclusions and recommendations.  National Academies Press,  122 pp, ISBN 978-0-309-59218-5. https://doi.org/10.17226/919

  • Venturini G, Bianchi GW, Diederichs M (2019) How to quantify the reliability of a geological and geotechnical reference model in underground projects. In: Rapid Excavation and Tunneling Conference 2019

  • Viola G, Venvik Ganerød G (2007a) Oskarshamn site investigation: atructural analysis of brittle deformation zones in the Simpevarp-Laxemar area, Oskarshamn, southeast Sweden, report from Phase 1: SKB P-07-41. Svensk Kärnbränslehantering AB, 77 pp. www.skb.se; http://www.skb.com/publication/1519038/P-07-41.pdf

  • Viola G, Venvik Ganerød G (2007b) Oskarshamn site investigation: structural characterization of deformation zones (faults and ductile shear zones) from selected drill cores and outcrops from the Laxemar area—Results from Phase 2: SKB P-07–227, Svensk Kärnbränslehantering AB, 154 pp. www.skb.se; http://www.skb.com/publication/1618788/P-07-227.pdf

  • Wellmann F, Caumon G (2018) 3-D Structural geological models: concepts, methods, and uncertainties. In: Advances in Geophysics, vol 59. Elsevier. Amsterdam, pp 1–121

  • Westland J, Busbridge JR, Ball JG (1998) Managing subsurface risk for Toronto’s rapid transit expansion program. In: Ozdemir L (ed) Proceedings of North American Tunneling ’98, Newport Beach, California, USA

  • Winchester S (2002) The map that changed the world. In: Willam Smith and the birth of modern geology, 2nd edn. Penguin Books, London, ISBN: 9780140280395, 352 pp

Download references

Author information

Authors and Affiliations

  1. Golder Associates & TGC Geo-Solutions, Oakville, Canada

    Trevor G. Carter

  2. SRK Consulting, Vancouver, BC, Canada

    Wayne P. Barnett

Authors
  1. Trevor G. Carter
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wayne P. Barnett
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Trevor G. Carter.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Carter, T.G., Barnett, W.P. Improving Reliability of Structural Domaining for Engineering Projects. Rock Mech Rock Eng 55, 2523–2549 (2022). https://doi.org/10.1007/s00603-021-02544-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00603-021-02544-6

Keywords

Search

Navigation