Safe Rapid drift development

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development within the underground metalliferrous mining industry in Canada ..... Underground Excavations, Proceedings 15th Canadian Rock Mechanics ...
Safe Rapid Drifting - Support Selection Fidelis T. Suorineni Mining Innovation, Rehabilitation and Applied Research Corporation – Geomechanics Research Centre, Laurentian University, Sudbury, Ontario, Canada Peter K. Kaiser Mining Innovation, Rehabilitation and Applied Research Corporation – Geomechanics Research Centre, Laurentian University, Sudbury, Ontario, Canada John G. Henning Placer Dome (CLA) Limited, Porcupine Joint Venture, South Porcupine, Timmins, Ontario, Canada

Abstract Rapid drifting enables quicker access to orebodies, higher production rates and a resultant reduction in production cost. The Mining Innovation, Rehabilitation and Applied Research Corporation (MIRARCO) funded by the Canadian Mining Industry Research Organization (CAMIRO) has developed a methodology for safe rapid drift development within the underground metalliferrous mining industry in Canada According to industry survey, about 36% of drift development cycle time is spent on support installation. MIRARCO has developed a methodology for safe rapid drift development based on minimizing time spent on support installation. The methodology includes a critical review of the rockmass classification systems, examination of current support practices in the mining industry and civil tunneling, review of rapid drift development practice in South Africa, introduction of risk hazard procedures to account for material property variability and the development of a WIZARD as a quick decision-making tool for the implementation of the procedures. A comprehensive field data collection procedure was put in place and data collected from various mines to verify and calibrate the support selection rationale. The findings of the research programme resulted in the development of an improved rockmass classification system and showed that construction effects have drastic influence on support levels but is often not accounted for in assessing support levels. Stress effects and structurally controlled failures are the other important factors to take into account in rapid drift development. Three support classes were established for safe rapid drift development as No Systematic Support, Light Support and Strong Support. The support levels took into account cost, rate of installation and safety based on compatibility with ground characteristics. This paper describes the methodology for safe rapid drifting within the underground metalliferrous mining industry in Canada and highlights the key issues and major drivers behind their continued development at the Geomechanics Research Centre within MIRARCO.

Introduction Rapid drift development improves a mines net present value (NPV) through quick access to orebodies, increased production and reduced mining cost. Available data from Canadian metalliferrous underground mines show that advance rates in single development headings are of the order of 0.5m/manshift, which translates into 120m/month. A survey by Laurentian University’s Mining Automation Laboratory (LUMAL, 1997) and Graham (per. Comm.) show that the greatest amount of development cycle time is spent on support installation. What is surprising is that the time spent on support installation is independent of whether the development process is automated or not. The results also show that time spent on support in the development cycle in mining is similar in civil engineering tunneling. Figure 1 compares development cycle activity times for automated and unautomated development processes in mining and with civil engineering tunneling. By reducing time spent on support installation significant improvements on drift advance rates can be achieved without adversely affecting safety




41% 21%


Ground support (a) Current development practice (LUMAL, 1997)


24% 16%






(b) Automated current practice (LUMAL, 1997)

Charging (c) Typical drill and blast tunneling practice (after Isaksson, 1988)

Figure 1 Drift development cycle activity time distribution. In December 2000 the Geomechanics Research Centre (GRC) in collaboration with researchers from Queen’s University and the University of Alberta, was invited by the Canadian Mining Industry Research Organization (CAMIRO) to submit a proposal for the development of a methodology for drift support design for underground hard rock conditions typically found in current mining practice in the Canadian Shield. The objective of the request was to search for a rationale for optimizing ground support systems installed in drift developments. The study was part of a major drive to promote safe rapid drift development and one of our goals was to minimize the time required to install adequate support during the development cycle. This paper presents the methodology developed for safe rapid drifting within the metalliferrous underground mines in the Canadian Shield. The scope of the project was limited to single widely spaced drifts by the project technical advisory committee. Hence, the procedures described here do not take into account mining-induced stresses or stress effects from nearby drifts and other excavations, i.e. long-term stability considerations. Drift spans of between 4 and 6 m are assumed.

Support Selection for Rapid Advance Traditionally, support installed during development is designed to accommodate anticipated long-term drift loading when mining-induced stress changes cause drift instability due to stress-driven or rockmass relaxation failures. Most often, this support greatly exceeds the short-term support requirements as schematically shown in Figure 2. Figure 2a shows that current drift support systems are mostly permanent or Strong Support (SS) with Light Support (LS) and No Systematic Support (NSS) rarely used. To safely reduce support installation times the No Systematic Support and Light Support classes must be expanded and use of Strong Support reduced, as schematically shown in Figure 2b. For long-term stability, additional support is suggested outside the development cycle. NSS LS Out-of-cycle support (if needed) SS

(a) Current support (b) Proposed support practice for rapid practice drifting Figure 2 Support classes for drift development: NSS – No Systematic Support, LS – Light Support, SS – Strong Support. In drift advance, six to twelve months of continuous face activity is needed. Within this time window only minimum support is required to maintain the development needs. The drift is a temporary excavation in this time window and requires only temporary support. The main elements needed to determine support demands are the excavation wall rockmass quality, stress level and excavation function. Rapid drift development can only be achieved when there is some optimum combination of these three factors, and when other non-support related factors (constraints) are properly managed during development. Support based on excavation function depends on the importance of the excavation and hence is very subjective. The term excavation wall rockmass quality emphasizes that the impact of construction must be considered and the virgin rockmass quality should not be used. Ironically, in recommendations for calculating factors included in the rockmass classification systems many researchers (e.g. Hutchinson and Diederichs, 1996; Brady and Brown, 1985;


Brown, 1981) unequivocally recommend that fractures caused by blasting (construction effects) be excluded from mapping data. Damage to excavation wall quality has a strong influence on the rockmass support demand. Hence, for rapid drifting it is essential that the excavation wall quality rockmass be rated properly to reflect the rockmass self-supporting capacity. Hence construction damage must be considered. The term stress level (SL) refers to the maximum (σmax) or minimum (σmin) tangential stress (Equation (1)) on the drift wall normalized by the rockmass uniaxial compressive strength (σc):

σ max = 3σ 1 − σ 3 σ min = 3σ 3 − σ 1


where σ1 and σ3 are the major and minor principal stresses respectively. Circular openings are assumed. In the following sections the procedures for properly characterizing ground conditions for rapid drift support selection are presented. The procedures are developed based on a critical review of the rockmass classification systems, support practices in the mining and tunneling industries in Canada and Europe, and rapid drifting experience in South Africa. The concept of effects of material variability in rocks was also considered vital and introduced to account for potential risk/hazards associated with this material property behaviour.

Rockmass classification systems The rockmass classification systems are critically reviewed for their applicability and effectiveness in reflecting a rockmass self-supporting capacity on exposure by construction and their amenability to providing good adhesive strength with the recently expanding application of thin spray-on liners (TSL) as an emerging new support technology. There are many rockmass classification systems in existence, only three of which are commonly used. The three commonly used rockmass classifications systems are the Rockmass Rating system (RMR) by Bieniawski (1973), Tunneling Quality Index (TQI or Q) system by Barton et al. (1974) and the Geological Strength Index (GSI) by Hoek, Kaiser and Bawden (1995). The following summarizes the limitations of the existing rockmass classification systems: (i) Most assume that all joint sets in the rock mass are continuous (e.g. Q-system, GSI) and hence underestimate the rockmass self-supporting capacity and introduce an unknown degree of conservatism. Other systems such as RMR which consider different levels of joint continuity weight all factors equal (ii) The effect of construction methods on rockmass damage leading to poor excavation wall rockmass quality, while long recognized (Hoek and Brown, 1988; Hoek et al. 2002) as a dominant factor is often not accounted for (iii) Experience with emerging support technologies such as TSL is not reflected in any classification systems (e.g. they do not account for adhesion capacity (iv) Those systems depending on rating factors (e.g RMR and Q) rely on atface data collection and thus are less suited for advance planning (v) Most systems are reliant on laboratory test data such as the uniaxial compressive strength and structure mapping but under emphasize the influence of geological and mineralogical differences even though these have a significant effect on the performance of rockmasses on exposure. They also influence the ability of rockmasses to develop sufficient adhesive strength with TSL.

Modified Q-rating system (Q*) A modified Q called Q-star (Q*) was introduced to better account for discontinuous joint sets in the rockmass to take advantage of the rockmass self-supporting capacity arising from rockbridges. Barton (1999, 2002) did not still correct for this deficiency in Q by introducing a uniaxial compressive strength in the Q-system. Diederichs and Kaiser (1999) demonstrated that 1% rockbridge area is equivalent to at least one cablebolt. Q* (Equation (2)) also increases the sensitivity of the Q-system to changes in rockmass structure.

æ RQD öæ J r* ö Q =ç J d ÷ç ÷ ç J ÷ç J ÷ è n øè a ø



where Jd is an adjustment factor depending on how many joint sets are continuous out of the measured joint sets. *

When all joint sets are continuous Jd=1. J r is the joint roughness number for discontinuous joints and is equal to Jr when the critical joint set is continuous. Note that Jr and Ja refer to joint alteration and roughness numbers for the joint set critical for excavation stability. Details of the method are presented in Kaiser et al. (2003).


Construction Effects Construction method and care has a significant impact on support demand. Blast damage was shown to cause overbreak of up to 40% in some drifts. Construction related rockwall damage reduces the excavation wall rockmass quality and increases support demand. This effect is often ignored in current support selection procedures. A procedure was developed in which a construction factor Cf similar to Hoek et al. (2002) disturbance factor (D) is *

used to adjust Q* (Equation (3)) to arrive at a more realistic rockwall quality ( Qc ) reflecting the quality of rock to be supported. Figure 3 is a chart for determinations of Cf. To reduce construction damage, well planned and executed perimeter blasting is recommended in rapid drift development.

Machine boring



Very good perimeter blasting (Stable rock surface, very high percentage of HCF (> 70%), very regular drift profile, check scaling effort, no overbreak)


Extremly good

Controlled / perimeter blasting (Stable rock surface, high percentage of HCF (30 - 70%), regular drift profile, check scaling effort, low (30% ) overbreak)


Very poor

Very good

Figure 3 Chart for construction factor Cf determination

Qc* = Q

*C f


Rockmass characterization for TSL adhesion capacity assessment A rating system for excavation wall surface conditions was developed to assess the adhesion capacity of TSL. The rating system considers rockmass quality, mineralogy, foliation, surface roughness, water content and weathering. Figure 4 shows key steps in the rating system.


Rock strength

Extremely strong

If medium strong to very strong, assess foliation and grain size

Extremely weak to weak

Good adhesion


No adhesion

Grain size Strong to very strong rock

Good adhesion

Moderate adhesion

Poor adhesion

Medium strong rock

Weakly developed foliation (strong to moderate foliation strength) + medium-coarse grains

Weakly developed foliation (strong to moderate foliation strength) + fine grains or Well to moderately developed foliation (strong to moderate foliation strength) + medium to coarse grains Weakly to well developed foliation (low foliation strength) independent of grain size

Moderate adhesion

Moderate adhesion

Poor adhesion

Figure 4 Excavation wall surface rating system for assessing adhesion potential of TSL

Stress Effects When mining at depth, stress-driven failures dominate (Stress-driven failures relate to rock strength and induced stresses and thus could occur at shallow depths). Hence, measures to effectively evaluate stress related support demands are critical. Existing measures for estimating insitu stresses are linear with depth and overestimate stresses at depth. At depth, stress profiles are more realistically represented by non-linear functions since stresses tend to equalize under pressure and temperature at depth in accordance with Heim’s rule. Figure 5 is proposed for estimating insitu stresses. Locally, insitu stresses vary widely. The vertical stress is proportional to overburden density and vary relatively little compared to the horizontal stresses. The effect of insitu stress variability and how to adequately manage the associated risk is well discussed by Martin, Kaiser and Christiansson (2003). The authors of the paper also ably discussed reliability of insitu stress measuring methods. Methods that involve large volumes of rock in the order of 1000 m3 of rock such as the under excavation technique (UET) (Wiles and Kaiser, 1994) and large scale convergence methods (Martin et al. (1996) are more accurate compared to methods involving smaller volumes of rock in the order of only 1 to 5 m3 such as the hydraulic fracturing and over coring methods. Rock Brittleness Martin (1993) showed that strength of a hard brittle rock is composed of cohesion and friction and that the two components are mobilized at different rates of deformation. For intact rock, cohesion loss must precede frictional strength mobilization. There are over 20 different definitions of rock brittleness summarized by Andreev (1995). Rock brittleness or rate of strength mobilization affects the peak, post peak, and pre-peak strength behaviour if cohesion is lost and friction mobilized. Hajiabdolmajid (2001) defined brittleness (IB) in terms of plastic deformation (Equation (4)):

IB = where

ε fp and ε cp are

ε fp − ε cp


ε cp

the plastic strains at peak frictional strength mobilization and minimum cohesive strength



Figure 5 Non-linear curves for estimating insitu stresses (Diederichs 2000). The concept of rock brittleness and its relevance to rapid drift development is dealt with by Chinnasane et al. (2004). Structurally controlled failures are dominant in low to intermediate stress regimes. Structurally controlled failures are accounted for by a wedge scaling factor method. Most wedge analysis procedures are conservative because of the inherent assumption that all joint sets in the rockmass are continuous. To facilitate rapid drifting at-face assessment, an observational approach for assessing the wedge-scaling factor was developed in addition to the theoretical method.

Support Selection Depending on the ground condition, three support classes were defined for rapid drift development. In some ground conditions support can be staged to enhance development rate by support staging. In support staging only 10 to 30% of the long-term support needs is applied to ensure safety at and close to the working face.

Support classes Three main support classes are defined for rapid drift development based on ground condition and support system capacity. The three classes are: (i) No Systematic Support (NSS) – NSS is applied when geomechanically no structural support is required, independent of regulatory and company policies, after all loose is removed by scaling. Safe working conditions can be achieved without support or with occasional spot bolting. (ii) Light Support (LS) – LS consists of areal coverage with TSL or tendon support. LS is applied when rockmass and stress conditions indicate that the rockmass needs help to enhance its self-support capacity for safe working conditions within the time frame of active development (iii) Strong Support (SS) – SS is a combination of areal and tendon support and is similar to what most mines currently consider standard support. SS may be TSL plus bolts, mesh plus bolts or shotcrete plus bolts. SS is used when rockmass and stress conditions suggest that the rockmass needs a lot of help in the form of structural reinforcement to be stable. Support systems Determining which support system is appropriate at a given time depends on the rockmass quality, stress conditions and sometimes drift function. TABLE 1 shows suggested support systems for rapid drift development.


TABLE 1 Support system classes and categories with examples Support class NSS LS Ultra light

Support system category NSS LS1 LS2

Support capacity Rockmass only Low capacity – tendons only Low capacity - Boltless


Moderate capacity – Tendons only Moderate capacity – Sparse bolted and TSL Moderate to high capacity




High capacity – Dense bolting pattern. Approx. 1.2 m2/bolt

Examples Rockmass Ultra wide pattern tendons TSL or fiber reinforced shotcrete (thickness