A numerical evaluation of using thin spray-on liners for coal mine gas management

Accepted Manuscript A numerical evaluation of using thin spray-on liners for coal mine gas management Zecheng Li, Furqan Hussain, Rudrajit Mitra, Serkan Saydam PII:

S1875-5100(17)30268-8

DOI:

10.1016/j.jngse.2017.06.022

Reference:

JNGSE 2220

To appear in:

Journal of Natural Gas Science and Engineering

Received Date: 28 February 2017 Revised Date:

23 May 2017

Accepted Date: 23 June 2017

Please cite this article as: Li, Z., Hussain, F., Mitra, R., Saydam, S., A numerical evaluation of using thin spray-on liners for coal mine gas management, Journal of Natural Gas Science & Engineering (2017), doi: 10.1016/j.jngse.2017.06.022. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT

A numerical evaluation of using thin spray-on liners for coal mine gas management Zecheng Li a, Furqan Hussain b,*, Rudrajit Mitra a, Serkan Saydam a b

School of Mining Engineering, UNSW Australia, Sydney, NSW 2052, Australia School of Petroleum Engineering, UNSW Australia, Sydney, NSW 2052, Australia

* Corresponding author. E-mail address: [email protected] (F. Hussain).

Abstract

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Gas drainage has been the most commonly used and also most reliable technique for underground coal mine gas management. However, due to the suction pressure applied,

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the air may migrate into the drainage boreholes through the fractures in the coal seam and dilute the drained gas. The low concentration gas may also lead to many other risks such as spontaneous combustion and gas explosion. For these reasons, various types of sealants are used to prevent the interaction between the mine environment and the coal seam. However, these sealants can only seal the space between the drainage pipes and the boreholes, while the internal fractures of coal seam cannot be blocked off by the

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sealing materials.

As a surface support tool, thin spray-on liners (TSLs) provide a promising potential for their operational benefits to reduce the mining cost. Besides ground support, TSLs also show potential to be used for coal mine gas management, due to their relatively low

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permeability characteristics.

This paper includes a numerical study to investigate TSL applications to improve the

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gas drainage efficiency in underground coal mines. A coupled simulation method was adopted in this study. The permeability variations due to mining disturbance were estimated by geomechanical modelling, while the gas flow within the coal seam was modelled with a commercial reservoir simulator. The model was first calibrated by history matching the gas production and gas concentration data in the study area to determine the unknown reservoir properties. Sensitivity analysis was then carried out on the calibrated model to predict the drainage borehole performance with different TSL application scenarios. Parameters studied in this study include TSL application length, application time, TSL permeability and coal permeability. The results from this study can be used to understand the effect of TSL applications on the gas drainage efficiency 1

ACCEPTED MANUSCRIPT and to assist the future operational capability of TSL applications in underground coal mines. Keywords: Reservoir simulation; Thin spray-on liners (TSLs); Gas management; Gas drainage.

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1 Introduction Coal seam gas (CSG), which is mainly composed of CH4, has always been considered as a threat for underground coal mining; as it is one of the main causes of gas outburst and explosions (Wang et al., 2012). Every coal mine has to take effective measures to

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control the gas concentration in the mine environment below statutory requirement (Karacan et al., 2011).

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Ventilation has been the first recourse for coal mine gas management (Noack, 1998) and a well-designed ventilation system can deal with low to medium gas emission problems (Thakur, 2006). When it is impractical to control gas concentration by ventilation alone, gas drainage using pre-drainage and/or post-drainage techniques has to be introduced to reduce the gas content and emissions (Brunner et al., 1997). Pre-drainage methods aim to reduce the gas content of coal seam before mining for the purpose of reducing gas

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emissions during development and longwall production. Post-drainage methods (also known as goaf or gob drainage) aim to capture gas during longwall phases to reduce the amount of gas managed by ventilation (Karacan et al., 2011). There are three main

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benefits that are associated with the gas drainage in gassy coal seams: an improvement in the mine safety by removing gas from the mine; a decreased environmental impact by reducing the greenhouse gas emissions; and the production of a relatively clean-burning

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energy source (Bibler et al., 1998; Warmuzinski, 2008; Karacan et al., 2011; Wang et al., 2012).

For underground gas drainage, a suction pressure is usually applied on the gas drainage system for two purposes: the suction pressure can prevent the gas leakage from the pipes into the underground environment and the suction pressure can help desorption of gas from the coal seam into the drainage boreholes. However, this suction pressure may also cause a low concentration of drained gas due to the ventilation air migration into the drainage boreholes through the fractures around the drainage boreholes (Xia et al., 2014a). The mining disturbance would further contribute to this migration process as

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ACCEPTED MANUSCRIPT the stress-induced rock fracture would increase the permeability of the coal seam near the roadway (Li et al., 2016b). The low concentration drained gas may also lead to many other hazards, such as spontaneous combustion of coal and gas explosion (Xia et al., 2014b). It is worth to point out that the sealing material that in the drainage boreholes can only seal the space between the drainage pipe and the borehole; however,

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the fractures within the coal seam cannot be sealed by the sealing materials (Lu et al., 2014).

A thin spray-on liner is defined as a thin (2-5 mm) chemical-based material that is applied onto the rock surface to support the mining excavations (Saydam et al., 2004;

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Gilbert et al., 2010; Ozturk, 2012). TSLs have been used in civil engineering as sealants many years before being introduced to mining industry. For mining industry, TSLs were

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initially designed as sealants to limit the weathering of rock and later were intended to be used as a substitute to mesh and shotcrete as a support tool (Yilmaz, 2007). Many TSL products are available on the market and they differ by the mixing types such as liquid/liquid or liquid/powder and by polymer-based type (Northcroft, 2006). The polymer-based TSLs can be characterised into the following six groups: (1) Acrylics, (2) Liquid latex where latex is any known polymer, (3) Polyurethane, (4) Polyurea, (5)

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Methacrylate and (6) Hybrid (Kaiser and Suorineni, 2006).

The advantages of TSLs include fast application rate, rapid curing time, reduced material handling, high tensile and adhesion strength, and the ability to penetrate into joints (Kuijpers et al., 2004; Pappas et al., 2004). These properties will ease logistics,

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improve on cycle times, increase mechanisation and improve safety through effective underground support (Stacey, 2001). Due to these operational benefits, TSL support has

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become popular in the mining industry since 1990s (Ozturk, 2012). Besides used as a ground support tool, TSLs also show potential to be used as a gas management tool in underground coal mines. Many tests have been conducted to investigate the permeability characteristics of TSLs and the permeability of TSLs were found in the range of nanodarcies (Archibald and De Souza, 1993; Maas and Renken, 1997; Saghafi and Roberts, 2001; Hussain et al., 2012). Li et al. (2016b) identified the potential use of TSLs as a gas management tool in underground coal mines: for gas emission control - TSLs may serve as a sealing skin to reduce the irregular gas emission from the coal seam into the mine environment; for gas drainage enhancement purpose -

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ACCEPTED MANUSCRIPT TSLs can prevent the ventilation air from migrating into the gas drainage boreholes and increase the drained gas purity. A field trial was conducted by Li et al. (2016c) in an underground coal mine, located in the Southern Coalfields of New South Wales Australia, to investigate the effect of TSLs on the gas drainage efficiency. The trial location was on the tailgate of a longwall panel

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between two adjacent cut-throughs. Fig. 1 shows the approximate locations of the gas drainage boreholes in relation to the gas drainage stub and other nearby longwall panels. In this field trial, TSL was sprayed onto the rib and roof areas surrounding the gas drainage boreholes. The TSL was expected to seal the fractures around the gas drainage

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boreholes and then reduce the ventilation air migration. It was found that the key benefits associated with the application of TSLs were the increase of gas purity and the

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decrease in the contamination.

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Fig. 1 Location plan of the test site (not to scale) (Li et al., 2016c).

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TSL application was found to have a favourable effect on the gas drainage borehole performance. However, due to the limitations of underground conditions, it was not feasible to investigate the effect of different TSL application scenarios in the field trials. Reservoir simulation has become a particularly useful tool to realistically represent the complex gas storage and production mechanism. Many simulators are available in the market and have been successfully applied for gas recovery from various coal basins using both vertical and horizontal wells (Young, 1998; Zuber, 1998; Karacan et al., 2007a; Karacan et al., 2007b; Karacan et al., 2008; Karacan and Luxbacher, 2010; Packham et al., 2011; Karacan, 2013; Karacan et al., 2014; Karacan, 2015).

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ACCEPTED MANUSCRIPT This paper describes a numerical study to investigate the effects of a TSL application on the gas drainage efficiency. A coupled method was adopted in this study by using a geomechanical modelling software, Fast Lagrangian Analysis of Continua in 3 Dimensions (FLAC3D) and a reservoir simulator GEM from Computer Modelling Group (CMG-GEM). The information obtained from the previous laboratory test results

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and field observations was integrated into this study. The objective of this paper is to investigate the effect of different TSL application scenarios to evaluate the gas drainage performance and gas emissions through a numerical approach. In this study, TSL

parameters.

2 Reservoir model development

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application length, application time, TSL permeability and coal permeability are used as

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A commercial reservoir simulator GEM was used for the simulation study. It is an efficient equation-of-state (EOS) compositional simulator that can simulate the dualporosity behaviour of coal seams for CBM/ECBM recovery (CMG, 2014). The model was developed and calibrated for the longwall mining area where the field trial was conducted. Li et al. (2016c) has provided a detailed description on the execution and results of the in-situ trial. However, some relevant details to this study has been

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summarised in the introduction part of this paper. The following sections describe the procedures followed to construct the reservoir model for the simulation.

2.1 Grid model of the study area and modelling parameters

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This study only considers the period before longwall panel extraction, and the main source of the drained gas is from the coal seam. Therefore, to simplify the simulation,

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the roof and the floor strata were not included in this simulation. The field survey results revealed that the coal deposit in the study area is almost horizontal. There is confidence that all the drainage boreholes are situated within the coal seam and no obvious geological structures exist that may influence the localised permeability or gas content in the coal seam. Therefore, the coal seam is simulated with a uniform thickness with no faults or dykes. A three-dimensional (3D) Cartesian grid consisting of three layers of the reservoir was constructed for the simulation study (Fig. 2). A 2.7 m thick coal seam was modelled by assigning a 0.9 m grid thickness for each of the layers. There are 67 × 49 grid blocks in the x and y directions, respectively, covering an area of 750 × 417 m2. The grid model 5

ACCEPTED MANUSCRIPT was constructed to include the details of the longwall mining environment. The first 3 grid blocks in the y-direction represent the roadway (Fig. 2). The size of the roadway grid blocks in the y-direction is 1 m, which makes the total width of the roadway equal to 3 m. The top 46 grid blocks in the y-direction represent the coal seam. The sizes of the coal seam grid blocks in the y-direction increase from 2 m (at the bottom) to 15 m

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(at the top). The sizes of the grid blocks in the x-direction increase from 0.5 m (closer to the horizontal wells in the middle) to 20 m (at the left and right boundaries). The variable sizes of the grid blocks were chosen to ensure the numerical stability as stated

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by Hussain et al. (2016).

Fig. 2. The horizontal cross-section of the 3D numerical grid used for the simulations (3 layers, at z = 2).

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The general reservoir parameters and their average values used for the base model are shown in Table 1. These parameters were obtained either from series of laboratory tests, field measurements and previous research reports. Stress redistribution is expected to occur in rocks surrounding the roadway, due to the roadway excavation. This stress redistribution would produce permeability variations in the coal seam (Adhikary and Guo, 2014a; Adhikary and Guo, 2014b; Hu et al., 2015). The permeability change due to the mining activities was estimated using FLAC3D which will be described in section 2.5. The calculated permeability was then used as inputs for the GEM model. During primary gas production, two distinct phenomena are associated with the reservoir pressure depletion, with opposing effects on coal 6

ACCEPTED MANUSCRIPT permeability. The first is an increase in effective stress under uniaxial strain conditions. The second is the gas desorption from the coal matrix, resulting in coal matrix shrinkage and thus a decrease in effective stress (Palmer and Mansoori, 1996; Shi and Durucan, 2004). In this study, the permeability change due to gas production was estimated by Palmer-Mansoori (PM) model that was integrated in the CMG-GEM code (CMG, 2014).

Parameters Seam thickness (m) Gas content (m3/t)

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Table 1 Basic reservoir parameters used for the simulation. Value 2.7 4

Langmuir volume CO2 (m3/t)

Source Site data Site data

Laboratory data

21.75

Laboratory data

Langmuir volume N2 (m /t)

10.9

Laboratory data

Langmuir pressure CO2 (kPa)

1456

Langmuir pressure CH4 (kPa)

2160

Langmuir pressure N2 (kPa)

3680 0.1-8

Langmuir volume CH4 (m /t)

Range of measured permeability x, y (mD) Range of measured permeability z (mD)

-1

Laboratory data (Li et al., 2016a)

0.27 45 0.05 0.01 0.008

Site data Site data Site data

0.013

(Zhou et al., 2013)

0.13

1.16 × 10-4

Cleat compressibility (kPa )

3

(Packham et al., 2011) (CMG, 2014)

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PM constant

Laboratory data

0.01-2

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Poisson’s ratio Reservoir temperature (℃) Matrix porosity Fracture porosity Max sorption strain N2 Max sorption strain CO2

Laboratory data

3.61×106

Young’s modulus (kPa)

Max sorption strain CH4

Laboratory data

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34.8

3

The relative permeability describes permeability behaviour with respect to the amount

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of water or gas within the cleat system (Connell et al., 2007). The simulator also requires interpretation of the water-gas relative permeability for modelling the gas drainage. The relative permeability curve was generated using the correlation function within the simulator which is given by:  S − S wr   krw =  w  1 − Swr  k rg

2

(1)

 S w − S wr = k rg _ max  1 −  1 − S wr − S gr 

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   

2

(2)

ACCEPTED MANUSCRIPT Where krw is the water relative permeability, krg is the gas relative permeability, Sw is the water saturation, Swr is the residual water saturation, Sgr is the residual gas saturation, and krg_max = max gas relative permeability. For this study, the following values were assumed for generating the relative permeability curve: Swr = 0.2, Sgr = 0, krg_max = 0.87 (Hussain et al., 2016). It is

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recommended that laboratory tests be conducted in the future to determine the actual relative permeability for better representing the reservoir characteristics.

2.2 Representation of the ventilation system

A method modified from Karacan et al. (2007a; 2007b) was used to simulate the

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ventilation system. Two horizontal wells were built into the grid model on either ends of the roadway to represent the ventilation airflow intake and return (Fig. 2). Nitrogen (N2)

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was injected into the horizontal well in the air intake side with a constant injection rate of 16.2 m3/s (air velocity: 2 m/s) to represent the typical ventilation airflow for the intake. The return horizontal well was designed to produce gas with a constant bottom hole pressure (BHP) of 1 atm. The permeability of the roadway area was set as 108 mD to minimise the ventilation frictional resistance in the roadway.

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2.3 Gas drainage boreholes simulation

The initial attempt was to model the ten-horizontal inseam methane drainage boreholes shown in Fig. 1. However, this would require larger dimension grid model as boreholes 2-8 extend more than one thousand metres along the maingate of the longwall panel. To

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simplify the grid system and to reduce the simulation time, only three methane drainage boreholes were included: boreholes 1, A and B (Fig. 2). The borehole layout was

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structured according to the field positions from the mine maps. Multilateral-well function of CMG-GEM simulator was adopted to simulate the horizontal-well branches. There are two sub-branches for borehole A and three sub-branches for borehole B, whereas only one branch was drilled for borehole 1. All boreholes were simulated as an undamaged and unstimulated well with a skin factor of 0 (Karacan et al., 2008). The diameter of these boreholes was 100 mm and a negative pressure of 15 kPa was applied on these gas drainage boreholes. The details of the gas drainage boreholes and related time information used for the simulation are shown in Table 2. The roadway was developed on 1/03/14, which was

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ACCEPTED MANUSCRIPT three months before borehole 1 was activated. Boreholes A and B were then completed subsequently.

Table 2 Specifications for the gas drainage boreholes. Position

Borehole 1 Borehole A Borehole B

Coal seam Coal seam Coal seam

Number of branches 1 2 3

Length inseam (m) 495 867 1014

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2.4 Simulating TSL application

Operation start date 16/06/14 26/09/14 10/10/14

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Borehole name

TSL was applied on the rib area surrounding the gas drainage boreholes with a

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thickness of 5 mm. The detailed description regarding the field TSL application can be found in the paper by Li et al. (2016c). This study modelled the TSL application by changing the permeability of the TSL area grids on the TSL application date. Fig. 3 shows the application of the TSL. Fig. 3b shows the scenario when 70 m length of TSL was applied. In other simulated scenario (not shown in the figure), TSL was applied 40 m and 750 m length of the roadway. For the base model, TSL was applied on

simulation date.

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15/10/2014 with a length of 40 m along the roadway i.e. after 7.5 months of initial

For field application, TSL was applied on the rib with a thickness of 5 mm and the permeability of the TSL material used was 5 × 10-6 mD (Li et al., 2016a). In this

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simulation, the grid thickness for simulating the TSL was set as 1 m to reduce the grid block numbers. To achieve the same gas blocking capacity, the TSL block permeability

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in the simulation was set as 1 × 10-3 mD, as the gas blocking capacity is proportional to the thickness of the TSL materials (Li et al., 2016a).

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Fig. 3 Plan view of the TSL application (a) no TSL application, (b) 70 m length TSL application.

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ACCEPTED MANUSCRIPT In order to verify the assumption that the gas blocking capacity is proportional to the TSL thickness can be achieved by the CMG-GEM, an additional simulation was run. A one-dimensional (1D) model was created using Cartesian grids. The grid system used for the base model was 85 × 1 × 1 in the x-y-z directions, as shown in Fig. 4. Grid sizes in the x, y and z directions were 1 mm, 26 mm, and 26 mm, respectively. Dead volumes

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were set at the inlet and outlet by using 10 grids. The coal sample and TSL were simulated by 60 grids and 5 grids respectively in the middle. The injection pressure was set 1 MPa and the production pressure was set 0.101 MPa. The injected gas was CH4.

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For the base model, the TSL permeability was 5 × 10-6 mD.

Fig. 4 The grid system used in the numerical model.

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Keeping the other parameters the same with the base model, the TSL thickness was increased to 10 mm, 100 mm and 1000 mm; while the TSL peamilities were decreased to 1 × 10-5 mD, 1 × 10-4 mD, 1 × 10-3 mD, respectively, as shown in Table 3. In order to

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compare the gas blocking capacities of TSLs with different thicknesses, reduction in the gas production rate and the pressure behind the TSL skin are compared. The comparison results are shown in Fig. 5. As can be seen in the figure, reduction in the gas rate and the gas pressure behind the TSL for different TSL thicknesses are almost the same, which indicate that the software can achieve the assumption that the gas blocking capacity is proportional to the TSL thicknesses.

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ACCEPTED MANUSCRIPT Table 3 TSL permeabilities with different thicknesses.

Scenarios

TSL thickness mm 5 10 100 1000

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Base model 1 2 3

TSL permeability mD 5 × 10-6 1 × 10-5 1 × 10-4 1 × 10-3

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(a)

Injection pressure Pressure behind TSL Production pressure

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Pressure (kPa)

1000

10

5

10

100

1000

TSL thickness (mm)

(b) Fig. 5 Gas rate and pressure behind TSLs with different TSL thicknesses.

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2.5 Geomechanical modelling of the permeability changes 2.5.1 Geomechanical model construction As an explicit finite difference program, FLAC3D has been extensively used by geotechnical, civil and mining engineers for stress and deformation analysis in soils,

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rock and structural support in three dimensions (Yasitli and Unver, 2005; Itasca, 2009; Xie et al., 2009; Chen et al., 2012). Therefore, FLAC3D code was used to evaluate the geomechanical response of the rock mass to roadway excavations.

The numerical model was built based on the geological conditions of the study area.

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The material properties and stratigraphic units were obtained either from the laboratory tests and field measurements or from previous site related reports (Waddington, 2002; MacGregor and Conquest, 2005; Keilich et al., 2006). The final parameters used in the

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simulation are given in Table 4. The numerical model for different lithology is shown in Fig. 6 (a). The model dimensions are 50 m (x-direction) × 50 m (y-direction) × 46.7 m (z-direction). The model is divided into 52,500 3D elements. The cross-section A-A shown in Fig. 6 (b) was chosen as the study area. The width of the roadway in the study area is 4 m, and half of the roadway is modelled by considering the symmetry

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conditions.

Table 4 Parameters used in the geomechanical modelling (Waddington, 2002; MacGregor and Conquest, 2005; Keilich et al., 2006). Thickness (m)

Bulk modulus (GPa)

Shear modulus (GPa)

Cohesion (MPa)

Friction angle (deg.)

Tensile strength (MPa)

2643

16

24.81

7.24

14.51

27.8

4.81

2600

20

17.07

11.44

19.4

33.3

7.87

1500 2539

2.7 8

2.62 16.76

1.42 6.51

2 17.1

25 28.9

0.84 5.65

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Wombarra shale Coal cliff sandstone Coal Loddon sandstone

Density (kg/m3)

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Rock

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Fig. 6. FLAC3D model (a) Grid model (b) Layout of the roadway (section A-A).

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ACCEPTED MANUSCRIPT 2.5.2 Stress and boundary conditions A comprehensive review of the regional in-situ stress has been compiled covering the same study area by Waddington (2002) as part of an Australian Coal Association Research Program (ACARP) research project. The results showed that the average ratio of major horizontal stress to vertical stress is about 2 in the study area, whereas the

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minor horizontal stress equals to the vertical stress. The direction of the major horizontal stress is approximately east-west, which is almost parallel to the direction of the roadway. The minor horizontal stress is perpendicular to the roadway.

The vertical stress was assumed to be directly dependent on the cover load. In the study

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area, the ground stress gradient is approximately 0.025 MPa/m (Waddington, 2002). By considering the top of the model was about 464 m below the ground surface, a

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compressive stress of about 11.6 MPa was applied to simulate the overburden load. The horizontal stress was initialized based on the stress ratio mentioned above. Model boundaries were set to represent the in-situ conditions as practical as possible. The displacements were fixed along the left, front and bottom sides of the model for x, y and z displacements, respectively. The other boundaries were modelled as free surfaces.

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2.5.3 Constitutive model

Previous research reveals that the coal measure rocks are elastic, plastic materials with strain-softening behaviour (Wang et al., 2011; Wang et al., 2013). A Mohr-Coulomb strain softening model was adopted in this simulation. This model has previously been

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proven as realistic for estimating the rock mass behaviour in underground coal mines (Badr et al., 2003; Xie et al., 2009).

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An empirical method described by Esterhuizen and Karacan (2005) was used in this study for setting the strain-softening parameters. The cohesion, dilation angle and tensile strength were allowed to decrease linearly with the increase of plastic strain. In general, the cohesion was reduced linearly to one tenth and the dilation angle was reduced from 10 ° to zero at the plastic strain of 0.5%. The tensile strength was decreased to zero after 0.1% of plastic strain. The friction angle remained the same after failure. However, further laboratory tests need to be conducted to determine the actual parameters for the strain-softening model.

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ACCEPTED MANUSCRIPT 2.5.4 Calculation of the permeability change Extensive research has been conducted to investigate the permeability of intact coal as a function of stress (Durucan and Edwards, 1986; Siriwardane et al., 2009; Liu et al., 2011; Wang et al., 2013; Alexis et al., 2015). Generally, the coal permeability decreases with the increase of stress before new fractures are generated. And an exponential

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relationship can be found between the permeability and effective stress. As coal fails and fractures occur, the permeability rises rapidly. The laboratory permeability results from Wang et al. (2013) show that the difference of permeability for intact coal samples and fractured coal samples are sometimes larger than 3 orders of magnitude.

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An empirical function was adopted in this simulation to calculate the coal permeability as a function of effective stress change. Compared with the relationship proposed by

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Esterhuizen and Karacan (2005), this equation considers the three-dimensional stress tensors (Liu and Rutqvist, 2009; Meng et al., 2011; Xue et al., 2011).

k = k 0 e − β ∆J

(3)

Where k is the permeability (mD); k0 is the initial permeability (mD); β is a constant determined by laboratory tests; and ∆ J is the first stress invariant (MPa) and are

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calculated as follows:

∆J =

∆σ1 + ∆σ 2 + ∆σ 3 3

(4)

Laboratory permeability tests were conducted on coal samples collected from the study

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area with different stress conditions. The permeability results of a coal sample as a function of first stress invariant is shown in Fig. 7. The constant β was determined to

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be around 0.5 from the permeability results by curve fitting method. It should be noted that the results were for one particular sample only, multiple tests are recommended to be conducted to determine the constant β .

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Fig. 7. Permeability results with different stress conditions.

For fractured coal permeability, Esterhuizen and Karacan (2005) assumed that the permeability is increased by 100 mD above the initial values once the coal fails in

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compression. Similarly, they assumed permeability to increase by 50 mD once shear failure along the bedding planes occurred. Their assumptions were based on the previously published values for jointed rock and fractured rocks (Hoek and Bray, 1981). Although some other findings were available for estimating the fractured coal

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permeability (Wang et al., 2011; Wang et al., 2013; Hu et al., 2015), the assumption made by Esterhuizen and Karacan (2005) was adopted in this simulation to estimate the

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roadway-induced permeability variations. This assumption was for field scale applications and it was found to have a better match with the field measurement results (Adhikary and Guo, 2014a; Adhikary and Guo, 2014b). The bedding shear failure was not considered in this simulation as only the strain softening model was used and no bedding properties were included in this simulation.

2.5.5 Results of the geomechanical modelling The stress redistribution obtained from FLAC3D and the calculated permeability results after roadway excavations are shown in Fig. 8. The vertical stress increases rapidly with distance from the rib due to the excavation-induced stress abutment and reaches the

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ACCEPTED MANUSCRIPT peak value at about 5 m from the rib. The stress concentration factor, defined as the ratio between the peak stress and the pre-mining in-situ stress, is about 1.5 for this condition. Based on the previous studies, this stress concentration factor normally ranges from 1.5 to 6 (Singh et al., 2011; Yang et al., 2011). After reaching the peak value, the vertical stress gradually decreases to the in-situ stress. With increasing

(

) increase from zero to the in-situ horizontal stress.

) and minor horizontal stress

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distance from the rib, both the major horizontal stress (

The excavation-induced permeability variations are calculated with Equation (3) and the results are also shown in Fig. 8 (a). Similar trends can be found for both the horizontal

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permeability (kx and ky) and vertical permeability (kz). The permeability near the rib is much higher than the original permeability due to the excavation-induced fracturing and

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stress relief. With the increasing distance from the rib, the permeability first decreases rapidly and then increase gradually to the pre-mining permeability. It is worthy to point out that a low permeability region exists in the coal seam. These calculated permeability results are then updated to the GEM simulator with an approximation (Fig. 8b) to

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calculate the gas and water inflow.

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20 15 10 5

H

h

V

0 10 Distance from the rib (m)

100

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(a)

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Stress (MPa)

25

(b)

Fig. 8. (a) Stress and (b) permeability results after roadway excavation.

3 Model calibration through history matching History matching of the observed laboratory or field data is generally used to estimate the remaining reservoir properties and to predict the future well behaviour (Zuber, 1998; Karacan et al., 2007b). For accurate history matching, water production and in-situ gas pressure need to be measured. However, it was not feasible to history match the water production as no field data were available. The field observation revealed that only 20

ACCEPTED MANUSCRIPT negligible water was produced in this area. Therefore, the methane drainage boreholes were assumed to produce a minimal amount of water in the study area. Fig. 9 shows the actual field and history matched data for coal seam production rate and drained gas concentration. High concentrations of ventilation air (10 to 40%) were observed from borehole 1. Initial attempts to history match ventilation air

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concentrations were not successful. Our previous work (Li et al., 2016c) show that fractures around the drainage borehole was the primary cause of high concentration of produced ventilation air. To model the high permeability region created by these fractures, higher permeability (Table 5) was assigned to 10 m × 12 m area around the

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boreholes (Fig. 10). The permeability in the fractured area was treated as history matching parameter. By modelling the fractures affected area, we were able to obtain

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good match for both coal seam gas production rate and coal seam gas concentration (Fig. 9). Gas drainage boreholes were produced at fixed bottom hole pressure (15 KPa). The history matching parameters included coal permeability, desorption time as well as the fracture permeability around the gas drainage boreholes. The final history-matched parameters are listed in Table 5. Only limited production data were available for boreholes A and B; therefore, history matching was only conducted on borehole 1.

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Table 5 History-matched parameters.

Parameters Permeability x, y (mD) k0 in Eq. (3) Permeability z (mD) k0 in Eq. (3)

Value 1.2 0.3 10

Desorption time CO2 (days)

10

Desorption time N2 (days)

7

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Desorption time CH4 (days)

800

Permeability of the fractured area z (mD)

200

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Permeability of the fractured area x, y (mD)

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1400 1200 Field Simulation

1000 800

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600 400 200 0

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Coal seam gas rate (m3/day)

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100 200 Time from the start of mining (days)

300

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0

(a)

80

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60 40 20

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Gas concentration (%)

100

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0

0

TSL application

Field Simulation

100 200 Time from the start of mining (days)

300

(b)

Fig. 9 Comparison of observed and simulated data for borehole 1 (a) coal seam gas flow rate and (b) gas concentration.

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Fig. 10 Fractures around the gas drainage boreholes.

4 Results and discussions

The calibrated model was used to evaluate the effect of TSL application on the gas

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drainage performance and gas emissions. Sensitivity analyses were conducted on various TSL application scenarios.

The gas production rate and drained gas purity results of borehole 1 for the base case are

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shown in Fig. 9.The gas production started immediately after borehole 1 completion and no drawdown was needed to initiate the gas production. The gas production rate

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increased dramatically to the peak value due to the initial high gas pressure gradient around the borehole. As gas was continually produced from the borehole, the gas production rate decreased slowly to the residual rate. Due to the existence of fractures around the gas drainage boreholes, the ventilation air migrated into the boreholes and diluted the drained gas concentration. The gas concentration for borehole 1 decreased to 60% before TSL application. After TSL application, a dramatic increase in gas purity can be found, with the gas purity value reaching about 90%.

4.1 Effect of TSL application length During the field trials, the TSL material was sprayed on the ribs surrounding the gas drainage boreholes with approximately 40 m length along the roadway. In this 23

ACCEPTED MANUSCRIPT simulation study, the effect of different TSL application lengths on the gas production rate and gas concentration was investigated. The TSL application lengths investigated in this study ranged from no TSL to whole roadway length TSL application (750 m). For all the simulation runs, TSL material was applied on the same day (day 228) and the only variable was the TSL application length.

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The gas production rate of borehole 1 with different TSL application lengths is shown in Fig. 11. The application of TSL slightly increases the gas production rate and an increase in TSL application length increases the gas production rate further. Fig. 12 shows the gas adsorption results of the coal seam with no TSL application and whole

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roadway TSL application. As seen in Fig. 12, the TSL application only influences the gas flow in the coal seam near the rib, whereas it does not have much influence on the

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gas flow in the coal seam far away from the rib.

Fig. 11 Coal seam gas production rate from borehole 1 with different TSL application lengths.

Fig. 12 Gas adsorption results of the coal seam at production day 275 (at z=2).

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ACCEPTED MANUSCRIPT The N2 production and gas concentration results for borehole 1 with different TSL application lengths are shown in Fig. 13. The N2 production rate represent the ventilation air production rate. The application of TSL reduces the ventilation air migration into the gas drainage boreholes. As seen in Fig. 13, with only 40 m of TSL application, the N2 production rate reduces from about 250 m3/day to less than

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70 m3/day. With the increase of the TSL application length, the N2 production rate is decreased further. It is worth to point out that there is a threshold TSL application length above which the N2 production would be reduced to zero. For this study, if the TSL application length is wider than 210 m, N2 production rate would be reduced to

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zero.

Normally, higher N2 production rate would result in lower concentration of drained gas.

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The drained gas purity results for different TSL application lengths are shown in Fig. 13 (b). As a result of the ventilation air migration, the drained gas purity was decreased to as low as 60%. The application of TSLs can increase the drained gas purity by reducing the ventilation air migration, and the gas purity increases with the TSL application length. Similar observations can be found with N2 production results: the drained gas

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purity will not be improved if TSL is applied wider than 210 m.

(a)

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(b)

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Fig. 13 N2 production rate and drained gas purity of borehole 1 with different TSL application lengths (nitrogen rate represent the ventilation air production rate, gas drainage started from day 107 and TSL applied at day 228).

N2 is produced as a result of the fractures around the boreholes and the negative pressure applied on the boreholes. If the ventilation air paths can be sealed, the N2 production rate can be reduced. The N2 mole fraction results at production day 275 for

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different TSL application lengths are shown in Fig. 14. With no TSL application, the N2 can migrate into the coal seam through the cracks around the gas drainage boreholes and dilute the drained gas purity (Fig. 14a). After TSL application, the N2 cannot migrate through rib area covered by TSL materials and the N2 migration path extended along the

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rib areas. The wider the TSL application, the further the migration path is extended (Fig. 14b, c and d); and at the same time, the resistance along the migration path increases.

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When the TSL application length exceeds 210 m, no N2 migration is observed in the simulation studies as the resistance along the migration path is too high for the N2 to flow (Fig. 14e, f and g).

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Fig. 14 N2 mole fraction in the fractures at production day 275 with different TSL application lengths (at z=2).

As discussed above, TSL application wider than 210 m does not seem to improve the gas drainage borehole performance further. In this section, the effect of TSL application on the rib emissions is analysed. Fig. 15 shows the rib emission results with different TSL application length. Without TSL application, the rib emission result follows a traditional rib emission decay curve with the residual rib emission rate of about 50 27

ACCEPTED MANUSCRIPT m3/day/100 m roadway (Moreby, 2005). When the whole roadway is applied with TSL material, the rib emission rate is reduced. The rib emission rate decreases as the increase of TSL application length and decreases to almost zero when the whole roadway is covered by TSL. For this study, the rib emission rate is not high and can be diluted easily with the ventilation system. However, when the roadway is drilled into the

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irregular high gas emission areas (such as areas near faults or dykes) and ventilation alone cannot dilute the gas concentration below the statutory level, TSLs may be applied on these areas to decrease the gas emission rate and let the roadway development continue. At the same time, supplementary gas drainage can be applied in

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these areas to reduce the gas content.

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Fig. 15 Gas emission rate in the roadway with different TSL application lengths (TSL applied at day 228).

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4.2 Effect of TSL application time Fig. 16 shows the N2 production rate and drained gas purity results with different TSL application time. The TSL application can significantly influence the N2 production rate and drained gas concentration. Before TSL application, the N2 production rate keeps at high values after borehole production starts. When TSL is applied, a dramatic decrease in N2 production rate is observed, as seen in Fig. 16 (a) for the blue line. If TSL is applied before gas drainage production, the N2 production rate will keep at low levels and the time of TSL application does not influence the N2 production rate, as seen in Fig. 16 (a) for the black and red lines. Similar trends can be found for the drained gas concentration results. After TSL application, the drained gas purity increases. If TSL is 28

ACCEPTED MANUSCRIPT applied before borehole production, the gas purity will keep at high values and an

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earlier TSL application does not seem to influence the gas purity further.

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(b)

Fig. 16 N2 production rate and drained gas purity from borehole 1 with different TSL application time (gas drainage started from day 107).

4.3 Effect of TSL permeability In this simulation, the effect of different permeability of TSLs on gas drainage performance was investigated. The permeability values in this simulation range from 10-5 mD to 0.1 mD. For all the simulation runs, the thickness of the TSL application was kept at 5 mm. 29

ACCEPTED MANUSCRIPT The N2 production rate and drained gas purity results are shown in Fig. 17. The applied TSL permeability influences N2 production and gas purity dramatically. The lower the TSL permeability, the lower N2 production and the higher drained gas purity are. However, if the TSL permeability is lower than 10-3 mD, then a lower permeability does not influence the gas production rate and drained gas purity further. As this permeability

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value means that the TSL is almost impermeable compared with the coal seam

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permeability.

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(a)

(b)

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ACCEPTED MANUSCRIPT Fig. 17 N2 production rate and drained gas purity from borehole 1 with different permeability TSLs (gas drainage started from day 107 and TSL applied at day 228).

4.4 Effect of coal permeability To investigate the possible effects of different coal permeabilities on the gas drainage performance and rib emission with TSL application, alternative coal permeability values

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were tested with this model. For this study, the permeability was increased to a maximum value of 10 mD and decreased to 0.01 mD. Other reservoir parameters and gas drainage borehole completions were held constant at their original design values.

The gas production rate results are shown in Fig. 18. The gas production rate increases

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with increase in coal permeability. For example, the peak gas production rate reaches to about 5000 m3/day with coal permeability of 10 mD. The results indicate that it is

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relatively easier to degas the coal seam of high permeability. Fig. 19 show the gas adsorption results for the reservoir after 100 days of drainage with different coal permeability values. For coal permeability of 0.01 mD, the coal seam is almost not degassed (Fig. 19a). The degassed area increases with increase in permeability. For

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10000 1000

0.01 mD

100

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0.1 mD 1.2 mD

10

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Coal seam gas rate (m3/day)

permeability of 10 mD, a large area of the coal seam is degassed as seen in Fig. 19(d).

10 mD

1

0

50 100 150 200 250 Time from the start of mining (days)

300

Fig. 18 Coal seam gas production rate from borehole 1 with different coal permeability (gas drainage started from day 107 and TSL applied at day 228).

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Fig. 19 Gas adsorption results for coal seam after 100-day drainage.

The coal permeability does not significantly influence the N2 production rate, as shown in Fig. 20 (a). However, the coal permeability can dramatically influence the drained gas purity, as shown in Fig. 20 (b), as the coal permeability can determine the gas flow rate within the coal seam. Lower coal permeability would result in a lower gas production rate; however, the N2 production is similar for different coal permeability

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values. For coal seam with permeability of 0.01 mD, the drained gas purity is only about 10% before TSL application; while this value is about 90% for coal seam with permeability of 10 mD. An increase in coal permeability would increase the drained coal seam gas concentration. It is also interesting to point out that the TSL application

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increases the drained seam gas purity regardless of the original coal permeability values, as seen in Fig. 20 (a). As long as the N2 production can be reduced, the drained gas

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purity will be increased.

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(b)

Fig. 20 N2 production rate and drained gas purity from borehole 1 with different coal permeability (gas drainage started from day 107 and TSL applied at day 228).

The rib emission results for different coal permeability values are shown in Fig. 21. The rib emission rate increases with increase in coal permeability values. For coal permeability of 0.01 mD, the average rib emission rate is about 10 m3/day/100m roadway. This value increases to about 500 m3/day/100m roadway for coal permeability of 10 mD. The higher the coal permeability value is, the higher rib emission rate would be experienced. 33

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Fig. 21 Gas emission rate from the roadway with different coal permeability.

5 Conclusions

This paper describes a methodology to analyse the effect of TSLs on the gas drainage efficiency by integrating the laboratory test results and field observations. A coupled

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simulation method was adopted in this study by using two commercial numerical modelling codes FLAC3D (a geomechanical stress analysis code) and CMG-GEM (a reservoir simulator). The model was built and run according to the actual operational schedule of roadway development and gas drainage borehole operations. The model was

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calibrated by history matching the gas production rate and gas concentration from the drainage borehole. Some of the results generated from this study may be site-sensitive.

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However, some generalisation can be derived from the results in understanding and predicting the effect of different TSL application scenarios on gas productions and rib emissions. The following conclusions are drawn from this study: (1) The stress redistribution induced by roadway excavation would significantly increase the coal permeability in the rib near the roadway. The ventilation air may migrate into the coal seam due to the suction pressure applied on the drainage boreholes and dilute the drained gas. (2) TSLs can be applied on the ribs surrounding the gas drainage boreholes and increase the resistance of the ventilation air flow path, thus, decrease the ventilation air production and increase the drained gas purity. 34

ACCEPTED MANUSCRIPT (3) Keeping other parameters constant, increasing the TSL application length decreases the N2 production and increases the drained gas quality from the borehole. When the application length was over 210 m, a further increase in application length would have a marginal effect on the N2 production rate and drained gas quality. However, an increase in TSL application length would reduce the rib emission rate.

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(4) An earlier TSL application would reduce the N2 production and increase the gas concentration from the borehole earlier. However, as long as TSL is applied before borehole operation, the application time would have minimal influence on the gas drainage borehole performance.

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(5) Modelling results showed that TSL with lower permeability would have a better effect in decreasing N2 production and increasing the drained gas quality. However, when the TSL permeability was lower than 10-3 mD, a further decrease in

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permeability would have a marginal effect on the gas drainage performance. (6) The permeability of coal seam plays an important role in the gas drainage performance. In this study, it was found that higher coal permeability would lead to a higher gas production rate and higher gas concentration. If the coal permeability is low, higher ventilation air dilution would be experienced for the gas drainage. The

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simulation results also demonstrated that the TSL application would improve the gas drainage performance using for various coal permeability values.

Acknowledgements

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The authors would like to thank CMG ltd. for making available the GEM simulator for this research. The authors would also thank Mr James Tenney for assisting with the in-

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situ TSL application and data collection. Constructive suggestions from Mr Duncan Chalmers from UNSW Australia are also acknowledged.

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We have run numerical simulations to show the effect of TSL on gas drainage efficiency Laboratory measured data and geotechnical modelling has been used to provide permeability data of coal and TSL. Simulations show that produced natural gas is more pure if TSL is applied

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