INTRODUCTION

During tunnelling, water ingress is reduced by grouting the rock mass. Rock mass grouting is dictated by rock mass conditions e.g., joints and fractures, and, consequently, these affect rock mass classification.

This article investigates the implementation of the Measurement While Drilling (MWD) fracturing index for rock mass characterisation and rock mass grouting during works on Tunnel 201 (T201) at the southern end of the Stockholm Bypass.

In the study, six rock mass grouting categories are defined, based on the rock mass condition, MWD fracturing index and grout consumption. The study shows that MWD data in combination of water loss tests could determine rock mass quality in 93% of the cases and grout consumption in 85% of the cases.

ROCK MASS

A tunnelling project starts with a site investigation to provide an understanding of the general rock mass conditions for the planned tunnel.

The rock mass data determines rock support and grouting classes as part of the tendering process. The most used rock mass classification systems today are the Rock Mass Rating (RMR), Q or GSI classification systems (Bieniawski 1973; Barton et al. 1974; Hoek et al. 1995, respectively).

Groutability can be determined based on two hydraulic conductivity domains – host rock (including minor alterations) and conductors (fracture zones) – (Kvartsberg 2013).

A conceptual model for the grout design of water-conductive fracture systems predicts grouting requirements (Hernqvist et al., 2012). These types of models should include the hydraulic head, fracture aperture, flow dimensions, fracture frequency and orientation.

In general terms, tunnel water ingress correlates to rock mass quality. Unfortunately, a direct correlation is difficult to obtain since rock classification systems can underestimate the impact of joint aperture, especially in the case of large open joints (Palmström and Broch, 2006).

In poor quality rock mass (low Q, RMR, etc.) grout consumption can be affected differently. With many fractures, the grout is expected to spread equally and eventually seal the rock mass reaching a pressure-based stop criterion. In the case of large, open fractures or a fracture zone, high grout consumption requires a change of rock mass sealing. On the other hand, (clay) filled fractures stop the spread of grout.

MWD

MWD technology evolves around collecting production machine data, including the following parameters: penetration rate (PR); feed pressure; percussive pressure; rotation pressure (RP); and, water flow (Van Eldert et al. 2020a).

The ‘noisy’ production data needs filtering and normalisation as discussed by Van Eldert et al. (2020b). The aim of the filtering is to remove faulty (unrealistic) values and produce comparable values along the drill holes, from different drilling booms and between different drill rigs. Figure 1 shows the effect of this filtering and normalisation method on penetration rate.

In addition, the process should remove collaring and coupling data, the effects of hole length and intercorrelated drilling parameters. The normalisation method for the data in this paper is based on regression lines in combination with a reference drill rig, drill hammer and drill rod.

The normalised data creates MWD indices e.g., fracturing index or drillability index. In general terms, the MWD fracturing index describes the rock mass heterogeneity and is mostly based on the penetration rate and rotation pressure (Schunnesson 1996, 1998; Ghosh et al. 2017; Van Eldert et al. 2021a, b). The drillability index is a normalised penetration rate.

Van Eldert et al (2021a) discussed the approach of relating MWD data to rock mass conditions. The best results were achieved with visual and holistic approach.

On the other hand, Martinsson and Bengtsson (2010) used single hole MWD fracturing index to improve rock mass grouting by allocating additional grout holes in areas with increased fracturing index. In addition, Høien and Nilsen (2014) correlated MWD indices and grout volume.

CASE STUDY

The Stockholm bypass will improve north-south road transport link around Stockholm, Sweden. The project is being developed by the roads authority, Trafikverket, abd consists of 18km-long double-tube main highway tunnels and almost 21km of auxiliary tunnels. This study concentrated on Tunnel 201 (T201) at the southern end of the Bypass, collecting data from grout umbrellas.

Rock extracted from the tunnels is mainly grey, medium to large-grained gneiss (Arghe 2016) within the rock mass foliated granite, pegmatite intrusions, greenstone veins, graphite, clay and several fracture zones were observed (Arghe 2016).

The rock mass quality was determined based on the Q-system. These class descriptions are shown in Table 1.

Zetterlund et al. (2017) established a comprehensive grouting plan prior to the excavation, based on previous experience in the city’s Norra Linken project (Martinsson and Bengtsson 2010). This plan incorporates MWD indices to adjust the grout hole layout and grouting procedures.

METHODOLOGY

The tunnelling cycle started by drilling 25m grouting holes ahead of the face formed by Epiroc XE3 or WE3 Boomers (see Figure 2). Drill rigs logged MWD data at 2cm to 3cm intervals.

An AMV Grouting Unit grouted the rock mass (see Figure 3). With the rock grouting process, the grout unit measured and logged the grout consumption per hole, through Bever’s Injecteringslogg, in xml format.

During the excavation, an engineering geologist mapped the drill and blast tunnels continuously (Qbase) and assigned a rock mass classification based on the criteria lined out in Table 1. Because of the possible communication between holes, the grout consumption, rock class and MWD indices (typical 15 to 20 grout holes) were compared on an umbrella-by-umbrella bases. To categorise the rock mass for the potential grout take, six categories were established based on expected MWD fracturing index (see Figure 4).

Drilling, grouting and rock classification data were collected from 97 grout umbrellas over 1.9km in T201, containing more than 2500 drill holes with reliable grouting and MWD data. A further 500m of tunnelling in the project’s tunnel T401 was processed to establish the validity of the correlation.

The MWD data were normalised after Van Eldert et al.’s (2020b). This normalisation and filtering process includes the filtration of the drill hole collar and coupling data points and the rod-dependent normalisation of the drill hole length and feed pressure for each rig and hammer.

MWD fracturing index (Equations 1 & 2), average grout consumption (L/m), and Qbase-value were established for each grout umbrella. Then, the parameter values were compared for each umbrella and each grout umbrella was assigned to the best fitting category. Finally, the categories were used to develop a conceptual method for the application of the MWD fracturing index and external information to determine pre-grouting requirements.

MWDvar=Σi N+i Σi N+iMWDi 1 N+1 -MWDi

Fracturing index = PRvar PR + RPvar RP

Where N: number of the considered additional sample (here, N=4)

MWDi: MWD sample value

MWDvar: MWD variation over 1:N

MWD: hole average MWD value, here PR and RP

RESULTS AND DISCUSSION

In Tunnel 201 (T201), there were more than 1.8 million MWD data samples obtained and then the fracturing index was calculated for each sample, individually.

The average grout consumption was calculated, in litres per metre, to be 3.57 L/m per hole for the first mode of the grout consumption distribution, with a standard deviation of 0.94 (see Figure 5). Of the 97 umbrellas investigated, 27 consumed, on average, high quantities of grout (≥ 5.5L/m per hole).

The grout consumption, Qbase-value and mean fracturing index for the grout umbrellas in Tunnel T201 are shown in Figure 6. Of the investigated umbrellas, 12 were rock class I (Qbase > 10), 25 rock class II (4 < Qbase ≤ 10), 45 rock class III (1 < Qbase ≤ 4) and 15 rock class IV (Qbase ≤ 1). An increased mean fracturing index (FI ≥ 1.15) was determined for 40 grout umbrellas.

In the majority of umbrellas, the rock mass quality, grout consumption and fracturing index are correlated, a low quality rock mass umbrella (Qbase ≤ 4) shows in general a high fracturing index (FI < 1.15) and high grout consumption (≥ 5.5L/m), and vice versa a competent rock mass showed a low fracturing index and low grout consumption for its umbrella. Several umbrellas did not align with this general observation.

The discrepancies are explained by fracture zones (high grout consumption, lower Qbase and lower FI at 14 umbrellas), high clay content observed during the mapping (low grout consumption, low Qbase and high FI at seven umbrellas) and intrusive dykes (low grout consumption, high Qbase and high FI at six umbrellas).

The categorisation of the grout umbrellas is described below.

Category A: no/few fractures – A total of 45 grout umbrellas with relatively high Qbase-value (Qbase > 4) and low grout consumption (< 5.5L/m). The tunnel sections had relatively few joint sets and fractures and the MWD showed a low mean fracturing index.

Category B: many fractures – In total, 23 grout umbrellas had a larger grout consumption (≥ 5.5L/m) and were mapped to have many fractures or a blocky structure (low Q, Qbase ≤ 4). These umbrellas showed a high mean fracturing index.

Category C: (large) fracture zone – Fifteen umbrellas, including three fractured intrusive dykes, consumed significant amounts of grout, and had fracture mapped. These zones had a low Q (Qbase ≤ 4) and were surrounded by favourable rock mass. These sections showed a locally high mean fracturing index locally while the overall fracturing index for the umbrella was low due to averaging out the MWD data of the entire umbrella.

Category D: few large, open fractures – One umbrella was mapped with only a few fractures and no clear fracture zones (Qbase > 4). Based on the rock mass description and MWD fracturing index this umbrella would have been assigned to category but its large grout consumption led it to be assigned to category D. The cause of the discrepancy is uncertain, this high grout volume could be caused by a few/single, large, open fractures. The precision of the MWD data is not good enough to establish the existence of some single fractures.

Category E: clay-filled fractures/weathered rock mass – Seven umbrellas displayed low grout consumption and low Q-values (Qbase≤4). The mapping of the tunnels after excavation showed severely weathered rock mass and significant amounts of clay. The high clay content in fractures and fracture zones results in a low Q (poor quality) rock mass and obstructs grout spread. The umbrellas showed a high mean fracturing index caused by alternation of clay filled joints and fractured rock mass. Based on the MWD and rock mass description, these umbrellas should be placed in category B but were assigned to category E because of the effect of the clay on the grouting.

Category F: intrusive dykes/textured rock masses – Six umbrellas showed a high fracturing index but with low grout consumption and were mapped as competent rock masses with intrusive dykes. If not for the high fracturing index, and based only upon MWD data, these umbrellas would be considered as category A or B but were given their own category, F. The researchers saw that alternating phenocrysts can falsely suggest a fractured rock mass in MWD data.

MWD fracturing Index

The MWD fracturing index showed to be a reliable predictor for the rock mass quality and, to a reasonable extent, the grout consumption. The exceptions are competent intrusion (dykes) having a high fracturing index but high Qbase and low grout consumption, and clay bearing fracture zones with a high fracturing index, low Qbase but low grout consumption.

The study showed that for 70% of umbrellas examined in Tunnel T201 the grout consumption had a good correlation with the fracturing index. This prediction correlation was effective for unfractured rock mass (low fracturing index, low grout consumption, category A, 46%) and also fractured (high fracturing index, high grout consumption, category B, 24%) rock mass.

When including local fractured zones (category C), MWD fracturing index can predict an additional 15% of the rock mass conditions.

However, the fracturing index showed to be unable to detect single large fractures (category D, 1%), because of the 2-3cm precision of the drill rig.

For fracture zones with high clay content (category E, 7%) and intrusive dykes (category F) there were increased variability in the drilling parameters (fracturing index) but not the generally accompanied grout spread. Inaccuracies may be reduced with the method by acquiring additional data during the excavation, e.g., water loss/gain index, based on pressure and flow (categories B, C, E and F), and observations of the flushing fluids from the drill holes (especially fluid colour, category E).

Concept procedure for grouting

Based on the presented results, a conceptual procedure was developed for tunnel excavations where lenient grouting requirements apply. In this situation, MWD fracturing index in combination with flushing (water) pressure and flow could be used to establish the grouting requirements.

Excavating into a moderately natural sealed rock masses with forgiving water ingress limits may not require rock mass grouting, e.g., a mining environment or under a natural water body. The conceptional procedure could reduce excavation cost because of savings in time, energy, and materials.

The proposed conceptual procedure is displayed in Figure 7. The procedure will be able to categorise the rock masses in categories A, E and F. These categories do not require substantial grouting and could be left ungrouted if tolerant water ingress limits apply.

The procedure starts off with probe hole drilling, during which MWD data are collected and the fracturing index is then calculated directly. If the fracturing index is low, no grouting is required (category A), except if significant losses of drill fluid occurs (category D).

In the cases where the fracturing index is relatively high, a water loss test should be performed, either by using the drill rig or a standard Water Pressure Test (WPT). The test will indicate if there is significant water in- or out-flow of the drill hole. With extensive water loss, pre-grouting of the fractured rock mass (category B) or fracture zone (category C) is needed. If the water loss test reveals insignificant flow, pre-grouting may be not required. Rock with high fracturing index can result from fractured rock masses with clay infill (category E) or competent intrusions/texture (category F).

CONCLUDING REMARKS

This study managed to correlate MWD fracturing index to the rock mass conditions (Qbase) and grout consumption. Discrepancies occurred in the case of competent textured rock masses (pegmatites, vein, or layered structures) which show a high variability in penetration rate resulting in a high fracturing index; in rock masses with clay filled structures (that hamper grout spread), and in cases with ‘large’ open fractures (>0.2mm) (Competent rock mass and low fracturing index but high grout consumption).

The study shows the concept could reduce the number of grouting umbrellas by employing MWD fracturing index and water loss tests. Based on the presented results, as found in the studies on Tunnel 201 (T201) of Stockholm Bypass:

? 93% of the rock mass quality could be predicted with the MWD fracturing index

? 85% of the grout consumption (high/low) could be predicted with the MWD fracturing index

? Water loss test can increase the accuracy of grout consumption prediction

? The proposed procedure may reduce grout activities by 59% (categories A, E and F).

? MWD technology gives additional information on the rock mass and should be included rock mass quality assessments, grouting decisions, and quality control during tunnel excavation

? MWD is not a replacement for current procedures, and rock mass characterisation and Water Pressure Test are required in high quality tunnelling projects.