3ASSESSMENT OF INFLOW POSSIBILITY INTO UNDERGROUND EXCAVATIONS USING DFN AND PERCOLATION CONSEPTS

M. Javadi PhD Candidate, Faculty of Mining & Metallurgical Engineering, Amirkabir University of Technology, Tehran, Iran

M. Sharifzadeh Asst.Prof., Faculty of Mining & Metallurgical Engineering, Amirkabir University of Technology, Tehran, Iran

ABSTRACT:

Control of water inflow into underground excavations during and after construction is a necessary operation due to the destructive influences such as adverse environmental impacts, mechanical instability, and impairing the project schedule. This paper discusses the applicability of DFN simulation for possibility assessment of water inflow into underground excavation in heterogeneous fractured rock masses. This process was performed using the statistics of field data of fracture geometry and FNETF computational code. The main input data for analysis were captured from site investigation and measurements in Siah Bisheh pumped storage project at the north of Iran. The powerhouse and transformer caverns were separated to different parts and the flow out from the rock into each part was individually measured during and after caverns construction. The possibility of ground water inflow into powerhouse and transformer caverns was estimated using percolation behaviour of DFN realizations and compared with observed one. Simulation results indicate that in order to come up with percolated caverns and inflow possibility, at least about 1-3% of fractures in the whole domain should be hydraulically active. In addition, maximum 38.6% of the total existing fractures in the domain contributed to flow. Comparison between simulation result and field observation indicates that, the DFN model predicted more possibility of water inflow into caverns than observed one. Since there is an appropriate correspondence between simulated and observed inflow possibilities in the less heterogeneous geological condition, existing impermeable zones around caverns can be considered as the one of the important reason of the overestimation of inflow possibility.

KEYWORDS: water inflow, possibility assessment, distinct fracture network, percolation.

1 INTRODUCTION Ground water inflow causes several difficulties such as unsafely, impairing the project schedule, mechanical instability, equipment damaging and altering the groundwater regime as well in the construction phase of any underground excavations as in the operation phase. To evaluate the related problems, the possibility and the probable water inflow into excavation must be somehow predicted in advance. Successful predictions can be of help in reducing the total construction cost and environmental impacts.

In many geological structures, the matrix permeability is negligible compared to permeability of fractures and rock mass hydraulic behaviour is controlled by fractures. In such highly heterogeneous fractured media, fluid flow takes place along preferential pathways within the fractures (Odling et al., 1999; Hitchmough et al., 2007) as field experiments provide indirect evidence of these preferential pathways (Wang et al., 1999, Hsieh and Neuman, 1985; Neuman and Depner,

1988; Novakowski and Bickerton, 1997; Nativ et al., 1999). Therefore, the classical continuous approach to the representation of fractured rocks, which is to model them as an equivalent porous medium, may become a poor approximation (Ubertosi et al., 2007), especially for near-field scale problems (Bear et al., 1993). Continuum behaviour is more likely to occur in densely fractured, well-connected fracture networks with mixed fracture orientations than in sparsely fractured, poorly connected, and/or strongly anisotropic systems (Niemi et al., 2000).

The possibility of ground water inflow into underground excavation in fractured rock is difficult to predict because of the complexity and heterogeneity of fracture network configurations. The existence of a flow pathway or connection between the boundaries of flow and underground excavation is a critical feature controlling the inflow possibility (Long and Billaux, 1987; Margolin et al., 1998; Darcel et al., 2003). The connectivity between fractures embedded in impermeable or low permeability geological formations in the

4M. Javadi, M. Sharifzadeh

surrounding underground excavation space is an important measure for assessing the possibility of ground water inflow and evaluation of the connectivity is fundamental to the problem (Xu et al., 2006). However, connectivity evaluation by performing the field experiment is restricted by time, resources, uncertainty of fractures geometrical parameters, and investigating a collection of interconnected fractures in an unknown volume and of variable directions. In such situations, the discrete fracture network (DFN) concept is an alternative to the discontinue representations of fractured rock mass and may appear much more adapted for analysis of the heterogeneous behaviour (Cacas et al., 1990). The DFN models possess wide applications for problems of fractured rocks (Long et al., 1982; Rouleau and Gale, 1987; Cacas et al. 1990; de Dreuzy et al. 2001; Baghbanan and Jing, 2008; Lee and Moon, 2004), due to the fact that it is, so far, an irreplaceable tool for modeling fluid flow and transport phenomena at the near-field scale because the dominance of the fracture geometry at small and intermediate scales can be approximated explicitly and in detail (Min et al., 2004).

The aim of this paper is to perform DFN method for possibility assessment of ground water inflow into underground excavations for near-field scale application. A new computational code so-called FNETF has been developed for generating DFN realizations. The main input data for analysis are captured from site investigations and measurements in Siah Bisheh pumped storage project at the north of Iran. The inflow possibility assessment and percolation behaviour along the powerhouse and transformer caverns were studied using the FNETF computational code and compared with water inflow fields data.

2 SIAH BISHEH PUMPED STORAGE PROJECT

2.1 Site Description and Geology

The Siah Bisheh pumped storage project is located at the Alborz serial Mountains, mainly folded and formed during the Alpine orogenic phase, with a NW-SE trend at the Western parts and NE-SW at the Eastern parts. Alborz Mountains is limited to the Central Iran to the South, and its Northern area is marked by some large faults.

The Siah Bisheh powerhouse cavern (hereafter named PHC) with 131.6 m length, 25 m width and 46.5 m height and transformer cavern (hereafter named TC) with 161 m length, 16 m width and 28 m height, are the main underground excavations in this project. Both PHC and TC were constructed at a depth of approximately 250 m below the ground surface with the azimuth of N152E. These caverns are located at the Permian formation that mainly consist of quartzitic sandstone, siltstone and shaly siltstone, dark and red shale and igneous rocks.

Thickness of these layers varies from some centimeters to 3.5 m. The attitude of the bedding planes has no considerable changes in dip and dip direction. There are uniform bedding throughout the powerhouse area with deep and dip direction of 55/195. It is noteworthy that during excavation of the powerhouse pilot , three shear zones with an almost 4050 cm thickness were encountered. All of these features are parallel to the bedding planes. The most important tectonic phenomenon of Siah Bisheh area is the fault called as the Main Thrust Fault with a dip/dip direction of 78/028 and an almost E-W trend (Lahmeyer-Iran Water and Power Resources Co., 2005).

2.2 Groundwater Level Three piezometer boreholes NGW1, NGW5, and NGW6 are considered for evaluating the hydraulic head distribution surrounding the PHC and TC. The location of these boreholes toward the caverns is shown in Fig. 1. The groundwater level in the piezometer boreholes were continuously monitored in different months.

The groundwater level in the NGW1 and NGW5 piezometr boreholes are available after January 2006 and it is available after December 2007 for NGW6. The maximum and minimum groundwater levels in the NG1 and NGW5 were recorded in October 2006 and May 2007. Since the groundwater levels in NGW6 are not available before December 2006, the maximum and minimum groundwater levels in this borehole were recorded in October 2007 and March 2007, respectively. Difference between the maximum and minimum groundwater levels in the NGW1, NGW5, and NGW6 are 25, 45, and 8 m, respectively. The maximum and minimum difference between groundwater level in the NGW1 and NGW5 boreholes are 130 and 180 m, respectively, and the average difference is 115 m. moreover, the maximum and minimum difference between groundwater level in the NGW1 and NGW6 boreholes are 20 and -1.8 m, respectively, and the average difference is 9.5 m.

2.3 Fractures Geometrical Characterization

Fracture's data collection was performed on the four vertical walls and the ceiling of the PHC. Fractures were mapped individually and for any observed fracture, trace length and orientation were recorded. Arrangement of the PHC walls establishes three perpendicular available mapping surfaces that provide a meaningful fracture sampling possibility with about total 13,500 m2 area in three-dimensional space and a total of 7,380 observed fractures.

All the recorded fractures were analyzed and grouped into three main fracture sets, here so-called M1, M2, and M3, based on the similarity of the orientation. A non-systematic class, here so-called

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M4, was considered for randomly oriented fractures that lie outside the limits of the three main sets. Each fracture sets were defined as described above by specifying a range of orientations in three-dimensional space. The Fisher orientation distribution is fitted to the measured data for the three main fracture sets. For non-systematic class M4, orientation is assumed to be a stationary random function independent of all other main fracture sets.

The fracture traces were designated for each main fracture sets and non-systematic class and analyzed statically. The analyses of fracture trace lengths from each sets and class suggested that the log-normal distribution is appropriate to describe trace length data. Fracture density is estimated from the observed fracture as the number of fractures per unit area. For each fracture sets and non-systematic class, the estimated statistical parameters of the orientation, trace length distributions, and fracture density, by considering the correcting for the biases, are shown in Table 1.

Figure 1. Location of piezometer boreholes NGW1, NGW5, and NGW6 surrounding the PHC and TC with two different types of vertical section S1 and S2 for inflow simulations.

Table 1. Statistical characterizations of the orientation, trace length, and fracture density for all fracture classes.

Parameter Fracture class M1 M2 M3 M4

Relative frequency 37.8 23.6 11.8 26.7

Fisher constant 12.34 2.64 16.3 ----* Fracture density

(m-2) 0.20 0.12 0.06 0.14

Mean trace length (m) 0.93 0.93 1.02 1.00

Trace length Std. 0.44 0.46 0.42 0.42 * For non-systematic class M4, orientation is

assumed to be a stationary random function.

3 SIMULATION WITH THE DFN

3.1 DFN Generation and Regularization

The usual practice in DFN modeling is to assume that most of the geometrical parameters of each fracture set can be statistically distributed. The numerical model developed for this study, so-called FNETF, uses a Monte Carlo approach to generate two-dimensional discrete fracture networks based on the statistics of the fracture-geometry parameters.

The individual fractures in the generation region are created one set at a time, and the number of fractures in each set is controlled by the areal density (number of fractures per unit area). A center point position for each fracture is determined by randomly selecting in the generation region. Fracture trace lengths are assigned with the cumulative probability density function of the trace length. The orientation of fractures is calculated using following respective cumulative probability density function, which is assumed to follow a Fisher distribution, as is commonly adopted in DFN modeling.

Fractures crossing the boundaries of the flow domain are truncated at the boundary and out of domain fractures are deleted. Because the generated fractures are finite, a relatively large number of fractures in the network may not be perfectly connected and some of them are not contribute in flow process. These hydraulically inactive fractures should be removed from the domain and can be recognized as isolated sub-networks and singly connected fractures, which have not complete interconnection between other percolating fractures or flow domain boundaries. Moreover, the dead-ends of the interconnected fractures are deleted and the network will be regularized. After this regularization, the DFN model becomes complete percolating graphs.

3.2 Simulation Domain

The DFN simulation in fractured media around both PHC and TC has been studied within two different practice cases through two different types of vertical section i.e. S1 and S2 as shown in Fig. 1. The type S1 section crosses over both PHC and TC, hence DFN and inflow possibility could be simulated around both caverns simultaneously. On the other hand, the type S2 section only crosses TC and as a result, it could only be used for possibility assessment of ground water inflow into TC.

A flow domain of 122m width and 129.75m height was used to assess possible inflow into both PHC and TC through section S1. The PHC with total width of 30m and height of 40m was located in the lower left edge, and the TC with total width of 16m and height of 28m was situated in the upper right edge of the considered domain (Fig. 2a). Then again a flow domain of 66m width and 88m height

6M. Javadi, M. Sharifzadeh

was used for possibility assessment of ground water inflow into TC through section S2 (Fig. 2b). The TC was located in the middle of the second domain in such a way that there was a 25m distance between vertical walls of the cavern and vertical boundaries of the domain and also a 30m distance between bottom of the cavern and lower boundary of the domain. The main input data for DFN generation such as orientation, trace length, and density of fractures are shown in Table 1.

With regard to the statistical nature of fractures geometry, a reliable analysis dictates that DFN realizations of the domain should be examined before launching the simulation procedure of water flow in the vicinity of caverns. Therefore, large number of DFN realizations shall be generated to ensure that the results are not dependent on specific fracture geometry arrangement and to produce more representative of stochastic behaviour of the fractured media. Consequently, 450 and 500 DFN realization models were generated around the caverns for possibility assessment of ground water inflow simulation in S1 and S2 sections, respectively.

4 RESULTS AND DISCUSSION

4.1 Simulation results

Heterogeneity of fractured media due to the stochastic geometry and the limited length of fractures is the reason why all fractures in the domain are not hydraulically active. Therefore use of the percolation concept is necessary for interpretation and analysis of simulation results. In order to have a percolated flow domain, there must be present an unlimited cluster of hydraulically active fractures in the flow domain. In order to observe water flow into a cavern (the so-called percolated cavern), at least one fracture member of the unlimited cluster must cross the cavern walls.

Following geometrical analysis of fracture network around caverns in section S1, three different states of percolation are observed. In some DFN realizations both PHC and TC are percolated simultaneously. In some DFN realizations neither is percolated and in some other realizations only one of the two is distinguished as percolated cavern. Simulation results show that 27 out of 448 total DFN realizations are not percolated at all while the remained 421 models (94% of the total) are partially percolated. Among the percolated realizations, in 56 models (12.5% of the total), only PHC is percolated, in 90 realizations (20% of the total) only TC is percolated and in 275 realizations (61.4% of the total) both are percolated. All in all, 331 realizations (74% of the total) have shown percolation for PHC and 365 models (82% of the total) have shown percolation for TC.

Figure 2. Flow domains for DFN simulation and possibility assessment of ground water inflow into caverns: (a) S1 cross section and (b) S2 cross section.

In every domain realization through section S1,

averagely 8,672 fractures have been generated. After removing fractures generated inside TC and PHC, on average, 7,975 fractures will be present in each flow domain realization. Amongst them, only a limited number is hydraulically active. Results of simulation for different states of caverns percolation have been summarized in Table 2. With regard to the results shown in Table 2, a general description can be derived for percolation behaviour in fractured network around caverns that can be discussed as follows.

722nd WORLD MINING CONGRESS & EXPO 11-16 September 2011 / ISTANBUL

To reach a percolated flow domain, there must be present an unlimited cluster of fractures in the flow domain in which fractures are hydraulically active. Therefore, in order to be observed water inflow in caverns there must be at least one fracture in the unlimited cluster membership that crosses the cavern walls.

By scrutinizing the minimum number of active fractures present in the domain for different DFN realizations, it is concluded that in order to come up with percolated PHC, there must be at least 103 (1.3% of the total) active fractures in the whole domain. For percolated TC this value is 85 (1% of the total) and to have both caverns percolated simultaneously, the minimum number of active fractures should be 275 (3.4% of the total).

The average number of active fractures in the domain for different geometrical models can provide a clue about the average size of the unlimited cluster present in the flow domain. Table 2, demonstrates that to have either of PHC or TC percolated, on average 15% of total existing fractures in the domain must be members of the unlimited cluster. It also shows that to have both caverns percolated simultaneously, on average 17% of total existing fractures in the domain must belong to the unlimited cluster. In addition, maximum 38.6% of the total existing fractures in the domain contributed to flow.

Table 2. Summary of simulation results for different states of caverns percolation.

Percolation state Number of active fractures Max. Min. Mean Std. All realizations 3079 0 1047.3 679.5

PHC percolated 3079 103 1225.7 640.3 TC percolated 3079 85 1190.8 640.4

Both PHC and TC percolated 3079 257 1349.7 606.4

Following geometrical analysis of DFN around

TC in section S2, two states of percolation are observed i.e. percolated and unpercolated TC. Simulation results show that 56 out of 500 total DFN realizations are not percolated while the remained 444 models (89% of the total) show percolation for TC. In every domain realization, averagely 3,180 fractures have been generated. After removing fractures generated inside TC, on average, 2,967 fractures will be present in each flow domain realization. Results of simulation for section S2 have been summarized in Table 3.

Based on the results shown in Table 3, it is concluded that in order to come up with percolated TC in section S2, there must be at least 90 (3% of the total) active fractures in the whole domain and on average 564 out of 2,967 total existing fractures (19% of the total) contributed to flow in the whole domain.

Table 3. Summary of simulation results for section S2.

Percolation state

Number of active fractures Max. Min. Mean Std.

All realizations 1359 0 501.2 307.5

TC percolated 1359 90 564.4 266

4.2 Observed inflow into caverns

The water inflow into caverns was measured during and after PHC and TC construction. The PHC and TC were separated to different parts and the flow out from the rock into each part was individually measured. In the PHC, the water inflow was observed and recorded in three different parts as 0+003 chainage (PI), 0+020 chainage (PII), and 0+071 to 0+085 chainages (PIII), which are shown in Fig. 3a. The water inflow was recorded in seven different parts in TC as 0+000 to 0+010 chainages (RI), 0+011 to 0+020 chainages (RII), 0+021 to 0+030 chainages (RIII), 0+031 to 0+040 chainages (RIV), 0+041 to 0+060 chainages (RV), 0+101 to 0+110 chainages (RVI), and 0+120 to 0+125 chainages (RVII), which are shown in Fig. 3b.

Figure 3. Variation of the measured inflow into caverns for different sections: (a) PHC and (b) TC.

8M. Javadi, M. Sharifzadeh

The flow out into PI shows a small water inflow of 0.4 Lit/min from February to May 2005 that increased suddenly to 2 Lit/Min on June 2005 and uninspiring after July 2005. For PII section, only a spring with 1.5 Lit/min inflow was recorded on June 2005. On the other hand, the flow out into PIII has been constantly observed during and after PHC construction.

In RVII section, an inflow with average rate of 0.5 Lit/Min has been recorded between November 2004 to August 2005 and from August 2005 to January 2006 there has not been observed any flow in this section. On February 2006, the inflow suddenly increased in this section and reached 2.5 Lit/Min, relating with increasing the water inflow into RI and RIV sections, and uninspiring after October 2006.

The recorded data in PI, PII, and RVII sections show a short-lived water inflow into the North part of the PHC. Since water inflow has been recorded in specific periods of time in these areas, it can be concluded that these sections of caverns are locally percolated and due to the low level of underground water, there is no water inflow. This release of groundwater level throughout the surrounding rock mass is related to construction activities that changes the groundwater in-site conditions and corresponding to an adjustment of the ground water level within the system. But in some specific time intervals, water inflow was recorded in these sections due to the increase in the level of underground water. As it was explained earlier in the text, there is much difference in groundwater levels of boreholes NGW1 and NGW6. However, the difference of groundwater level between boreholes NGW1 and NGW5 is manifest as compared with that of boreholes NGW1 and NGW6. Therefore, it can be concluded that a sudden fall (discontinuity) in groundwater level is anticipated within NGW1 and NGW5 boreholes and the North part of caverns is locally unsaturated.

4.3 Comparison Between Results

Regarding to saturation state of caverns, only the South part of cavern from 0+062.8 to 0+131.6 chainages of PHC (equal to 0+034 to 0+096.8 chainages of TC) is selected for comparison between DFN simulation in S1 section and observed percolation results. Comparison between observed and section S1 simulation results for different states of caverns percolation have been summarized in Table 4. Throughout this caverns part, observed water inflows indicate that 22.2 and 57.3 percents of total length have percolated state for TC and PHC, respectively. In addition, 18.7 % of total length is not percolated at all for both PHC and TC. The same calculated values from DFN simulation in section S1 are 74%, 82%, and 6%, respectively.

Comparison between DFN simulation in S2 section and observed percolation results is

performed for the South end part of TC form 0+0 to 0+034 chainages. Water inflow has been observed in all length of this part of TC while 89% of the total length of this part showed percolated state in DFN simulation.

Comparison between results indicates that for S1 section, the DFN simulation predicted more possibility of water inflow into caverns than observed one. Existing impermeable zones around caverns in this area can be considered as the one of the important reason of this behaviour; a presume that should be analyzed using maps and geological sections. A number of geological features exist in the area that can have relationship with this ground water behaviour in PHC and TC. Among them, one can mention presence of a sliding fault in the chainage of 0+080 in PHC with dip/direction of 70/305 and its tail in chainage of 0+105 in TC, shear zones, and igneous dykes that are also related to anticipated discontinuity in groundwater level. In addition, there is an appropriate correspondence between inflow possibility through S2 section DFN simulation and the observations, which are related to the less heterogeneous geological condition in this part of TC.

Table 4. Comparison between observed and simulation results through section S1.

Percolation state Percolation Length (Percent of Total)

Observed Simulation PHC percolated 22.2% 74%

Just PHC percolated 22.2% 12.5% TC percolated 57.3% 82%

Just TC percolated 57.3% 20% Both PHC and TC

Percolated 0.0 61.4%

Both PHC and TC Unercolated 18.7% 6%

5 CONCLUSION In this paper, the applicability of DFN realizations for possibility assessment of water inflow into underground excavation constructing in heterogeneous fractured rock masses is discussed throughout near-field scale domain. A new computational code so-called FNETF has been developed for generating DFN generation and regularization. The main input data for analysis are captured from site investigations and measurements in Siah Bisheh pumped storage project at the North of Iran. Due to the negligible matrix permeability of rock mass surrounding powerhouse and transformer caverns, DFN model was selected to assess possibility of water inflow. The PHC and TC were separated to different parts and the flow out from the rock into each part was individually measured during and after caverns construction. The DFN

922nd WORLD MINING CONGRESS & EXPO 11-16 September 2011 / ISTANBUL

simulation in fractured media around both PHC and TC has been studied within two different practice cases through two different types of vertical cross section i.e. section S1 crossing over both PHC and TC, and section S2 crossing over only TC. The possibility of ground water inflow into caverns was estimated using percolation behavaiour of DFN realizations in S1 and S2 sections and compared with observed water inflow fields data.

Following geometrical analysis of fracture network around caverns in section S1, three different states of percolation are observed. In some DFN realizations both PHC and TC are percolated simultaneously. In some DFN realizations neither is percolated and in some other realizations only one of the two is distinguished as percolated cavern. To reach a percolated flow domain, there must be present an unlimited cluster of fractures in the flow domain in which fractures are hydraulically active. Simulation results in section S1 show that in order to come up with percolated cavern, at least 1.3, 1, and 3.4 percents of fractures in the whole domain should be hydraulically active for PHC, TC, and both PHC and TC, respectively. In addition, maximum 38.6% of the total existing fractures in the domain contributed to flow. Observed water inflows indicate that 22.2 and 57.3 percents of total length have percolated state for TC and PHC, respectively. In addition, 18.7 % of total length is not percolated at all for both PHC and TC. The same calculated values from DFN simulation in section S1 are 74%, 82%, and 6%, respectively. Comparison between results indicates that, the DFN simulation overestimated the possibility of water inflow into caverns than observed one for S1 section. Existing impermeable zones around caverns in this area can be considered as the one of the important reason of this difference. On the other hand, water inflow has been observed in all length of the South end part of TC, while 89% of the total length of this part showed percolated state in S2 section DFN simulation. Comparison between results indicates that there is an appropriate correspondence between inflow possibility through S2 section DFN simulation and the observations, which are related to the less heterogeneous geological condition in this part of TC.

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