DEVELOPMENT OF A NEW INDEX FOR METHANE DRAINAGEABILITY OF A COAL SEAM USING THE FUZZY ROCK ENGINEERING SYSTEM

Coal seam gas is one of the most significant energy resources in unconventional gas fields. The identification of influenc- ing parameters and methane drainage assessment are, thus, a prime geotechnical focus for all potential methane drain- age projects. In methane drainage operations of coal seams, many factors, such as natural factors and operational factors affect the drainage efficiency. In this paper, a new coal seam methane drainageability index (CMDI) is introduced for pre-drainage techniques in a working mine. In this approach, seventeen parameters are considered as the main factors affecting the methane drainage form coal seam, and the interaction matrix based on the fuzzy rock engineering system (FRES), which analyzes the interrelationship between the parameters affecting methane drainage activities, are used to study coal seam methane drainageability. Since the value of interaction in the RES method is not unique, the fuzzy sys- tem is used to minimize subjectivity of the weights which are computed in the RES method. The Tabas coal mine (Iran) was selected as a case study and the proposed index was used to rank the C1 seam in this mine. It was observed that the methane drainageability index could suitably predict the potential of the methane drainage of coal seam. The newly proposed index can be used as a basis for decision-making when uncertainties about the evaluation of the parameters affect the methane drainage of a coal seam and reduce the risk of methane drainage projects.


Introduction
Coal seams may contain 60% to more than 95% methane that depend on the presence of other gases in the coal seam Darling, 2011;Wilson et al., 1995;Hamawand et al., 2013). Coalbed methane (CBM) also known as coal seam gas (CSG) is a natural gas that is stored (adsorbed) in coal seams. In the coal mine methane (CMM) method, gas is captured in working coal mines by underground or surface and underground methane drainage techniques to ensure the safety of a mine. In the enhanced coalbed methane (ECBM) method, the CO 2 is injected into the coal bed and the methane gas is released by some chemical reactions and then it is extracted by a drainage operation (Thakur, 2014; Gale & Freund., 2001;Wong et al., 2007;Karacan et al., 2011). CBM production behavior is complex and difficult to predict or analyze especially in the early stages of recovery. This is because gas production from CBM reservoirs is governed by a complex interaction of single phase gas diffusion through a matrix system and two-phase gas and water flow through a cleat system that are coupled through a desorption process ( Aminian et al., 2004). Coal mine methane can create a serious threat to mining safety and productivity due to its explosion risk. Methane drainage from a coal seam is used to improve the safety of coal mine extraction, reduce greenhouse gas emissions and improve mine economics by allowing a mine to produce coal with minimum methane levels (Warmuzinski, 2008;Flores, 1998;Sereshki, 2005;Comfort et al., 1999).
Methane drainage methods involve the removal of methane prior to mining activity on a virgin coal seam and during extraction. The objective methane drainage caused increases the amount of gas removal from the underground mining districts and hence minimizes the gas flow into the mine airways (Diamond, 1994;Thakur, 2014). Based on the degree of gasification of a coal seam and discontinuities in overburdens, vertical boreholes, horizontal boreholes, gob gas ventholes and inclined boreholes can be used for methane drainage. The specifications of boreholes such as the number of boreholes, orientation, spacing, location and gasification time depend on the coal seam properties and other special conditions (Black, 2011;Diamond, 1994 seam methane drainage is influenced by various factors which are divided into two categories: geological and operational factors. The success of drainage operations is dependent on these factors. Numerous studies have attempted to investigate the effect of various factors on methane drainage from a coal seam. Karacan analyzed methane emission data from U.S longwall mining using multiple regression analysis and a neural network. The principal component analysis (PCA) was used to determine the weight of each parameter on methane emissions. PCA test models showed that gas content and seam thickness have the highest effect on gas emission from a coal seam (Karacan, 2009 a,b). Karacan analyzed the total gas flow rates and methane percentages from gob gas ventholes using a multilayer-perceptron (MLP) type artificial neural network (ANN). Also the sensitivity analysis was performed to determine the most important variables that affect venthole productions (Karacan, 2009). Karacan developed an expert classification system for U.S longwall degasification system selection. This model can be used as a decision tool for degasification system selection using site-and minespecific conditions (Karacan, 2009). Hemza et al. considered ten factors influenced on methane content of coal beds Czech Republic. Numerous analyses were performed to study the relationship between these factors and gas content (Hemza et al., 2009). Dougherty and Karacan discussed methane control and prediction (MCP) software which was developed by NIOSH. This software can determine the type of degasification system, predict the production performance of a gob gas venthole, predict ventilation emissions from longwall mines and predict the dynamic elastic properties of coal (Dougherty and Karacan, 2011). Black studied the relationship between gas production from underground inseam drainage boreholes, coal seam properties and op-erational factors. The results indicated that the degree of saturation and drainage time has a significant impact on gas production (Black, 2011). Dai et al. studied the effect of geological factors such as effective trapping thickness, moisture content and ash content on coal seam gas content. They used support vector machine (SVM) theory to set up a nonlinear prediction model for gas content prediction between coal seam gas content and main controlling factors (Dai et al, 2013). Zawadzki et al. estimated the methane content of a coal mine using multivariable geostatistic simulation. The desorption factor and coal strength index, both of which were used in cokriging and sequential Gaussian co-simulation (Zawadzki et al., 2013). Liu et al. studied the effect of various factors on CBM productivity using the analytic hierarchy process (AHP) method. The results indicated that the weight of geological factors, engineering factors and drainage factors are 50%, 25% and 25%, respectively (Liu et al., 2014). In all those methods, the researchers did not consider all the parameters and their interactions completely.
There is an important point in methane drainage from a coal seam and its affecting parameters on each other. For example, increasing the value of one parameter causes an increase or decrease in the value of other parameters. Therefore, it is necessary to consider all parameter interactions completely. The interactions of some parameters in methane drainage are shown in Table 1.
Predicting the capability of a coal seam for methane drainage is an important issue in methane drainage systems. Therefore, the development of a new index that can classify the coal seam capability drainage by considering the interactions of influencing parameters is important. In such systems, the interactions of all influencing parameters (geological and operational) must be considered simultaneously. The rock engineering system (RES) approach can be used for the analysis of coupled mechanisms in rock engineering problems (Hudson, 1992). In this approach, the main factors are listed along the main diagonal elements of a matrix, also called the interaction matrix, and the interrelations between pairs of factors are identified in off-diagonal elements. Many researchers have studied  The aim of this research is to propose a new index for assessing the drainageability of a coal seam using the fuzzy rock engineering system. Therefore, by using the FRES method first, the parameters with the highest effect on the methane drainage are found and then a new index is presented to predict the coal seam methane drainage potential for pre-drainage techniques.

Factors influencing methane drainage
In the first step, the parameters that influence the methane drainage have been identified. According to lit-erature and various studies, the most important factors influencing methane drainage from a coal seam can be categorized into two types: natural factors and operational factors. These parameters are shown in Figure 1.

Rock engineering system
The concept of the rock engineering system (RES) approach was first introduced by Hudson for solving complex engineering problems. This approach can be used for the analysis of coupled mechanisms in rock engineering problems (Hudson, 1992). The RES uses a top-down analytic model to treat the rock mass, the boundary conditions, and the engineering activities as a complete, interactive, and dynamic system. The key element in the RES method is the interaction matrix. The interaction matrix is a basic technique for characterizing the important parameters and the interaction mechanisms in a rock engineering system. In the interaction matrix, all parameters influencing the system are arranged along the leading diagonal of the matrix, called the diagonal terms. Otherwise, the influence of each individual parameter on any other parameters is included at the corresponding off-diagonal position of the matrix. The off-diagonal terms are assigned numerical values which describe the influence degree of one parameter on the other parameters. Assigning these values are usually referred to as "coding the matrix". Several coding methods have been developed for this purpose, with the most common being the 'expert semi-quantitative' (ESQ) coding method (Hudson, 1992). ESQ coding has been used in nearly all previous works. In this method, one unique code is assigned to each interaction, thereby expressing the influence of a parameter on another in the matrix. Typically, coding values vary between 0 and 4 with 0 indicating no interaction, 1 indicating a weak interaction, 2 indicating a medium interaction, 3 indicating a strong interaction and 4 indicating a critical interaction. An interaction matrix is illustrated in Figure 2. After coding the interaction matrix by inserting the appropriate values for each off-diagonal cell of the matrix, the influence of each parameter on the system is named "cause" (Ci) and the effect of the system on each parameter is named "effect" (Ei) (see Figure 2). The C-E diagram is created by (C i , E i ) coordinate values plotted in cause and effect space. From this diagram "less interactive" and "more interactive" parameters are determined (Hudson, 1992).

Coal seam methane drainageability index (CMDI)
As mentioned in section 2, many parameters affect coal seam methane drainage. In this study, seventeen pa-rameters are considered as the main factors affecting the methane drainage from a coal seam and the importance and physical ranges of parameters, also the corresponding ratings, are listed in Table 1. It is notable that the values of the parameters are divided into five classes and each class ranges from 1 to 5. The ranges of parameters in Table 2 were proposed based on the judgments of experienced experts in field methane drainage and also the results obtained from literature review.

Definition of the coal seam methane drainageability index (CMDI) using the fuzzy rock engineering system
As previously mentioned in the ESQ coding method, one value is deterministically assigned to each interaction. Therefore, in order to consider the uncertainties of the influence of one parameter on the others, the "Fuzzy ESQ" (FESQ) coding approach was used.
The first step is to form the interaction matrix between effective parameters on coal seam methane drainageability. Then, questionnaires were prepared and ten experts were asked to determine the value of the interaction between each pair of parameters.
In order to defuzzify the interaction matrix, for each element of the matrix, the number of each state of interaction based on the experts' decisions is considered. The states of interaction are named as n A (number of no interaction), n B (number of weak interactions) , n C (number of medium interactions) , n E (number of strong interactions) and n F (number of critical interactions). These values are firstly normalized and then used as the input of the fuzzy system. For each fuzzy system input, two fuzzy sets "Low" and "High" are considered which are shown in Figure 3. For example, if n F is "Low" this means that most of the experts stated there is no critical interaction, and the probability of mode F (critical interaction) is lower (Rafiee et al. 2015).
When the normalized value for each element in the interaction matrix is less than 0.4, the MF (membership function) value of "Low" set is greater and the MF value of "High" set is lower and vice versa. It is noteworthy, the choice of the "Low" and "High" membership function for each input of fuzzy system have been appointed based on the experts' judgment (Rafiee et al. 2015). To increase the precision of the intermediate state of the output, the m 1 to m 9 fuzzy sets are defined between 0 and 4 for output of the fuzzy system. The output of fuzzy system form is shown in Figure 4. According to five inputs and considering two modes for each input, 2 5 rules could be defined. In Figure 5, a fuzzy system with 5 inputs, one output and 32 rules is shown. Considering the fuzzy system, the RES interaction matrix can be coded. Afterward, by using the value of parameters and their corresponding 'weights', the methane drainageability index for a coal seam can be calculated.
Hudson proposed a method for determining a weight for each parameter. For this purpose, in the first step, the cause (C i ) and effect (E i ) values for each parameter in the system is calculated by Equation 1 and 2 (Hudson,  1992). (1) ( 2) Where: I mn -interaction matrix element C i -sum of the raw values E i -sum of the column values for each parameter Then, the weight of each parameter is determined using following Equation 3 (Hudson, 1992). (3) Where: MP i -The rating value assigned to the different category of the parameter i. Therefore, the weight for parameter i, which is shown by w i , is calculated by its 'parameter interaction intensity' (C i + E i ) divided by the sum of interaction intensities of all parameters in the system (Hudson, 1992). After the weights for all parameters (w i ) were calculated, the coalbed methane drainageability index (CMDI) is calculated by Equation 4.

(4)
Where: w i -weights of parameters P i -assigned values to each input parameter considered for coal seam methane drainageability.
In the following section, the proposed coal seam methane drainageability index (CMDI) is calculated for the Tabas coal mine and is used to assess the coal seam methane drainageability.

Case study: Tabas coal mine
The Tabas coalfield is one of the most important coalfields in Central Iran. The area is located in the central desert of Iran, very far from any inhabited areas. The Tabas coalfield consists of the Mazino, Parvadeh and Nayband coal deposits. Coal-bearing strata in the Parvadeh deposit are within the Triassic formations. The rank of the Parvadeh deposit is anthracite and all of the coal seams are formed within the complicated monoclines and synclinal folds. The geology of the area is within a syncline which has been deepened to the east, and has been cut by several faults. Parvadeh coal deposit consists of five coal seams (C 1 , C 2 , D, B 1 and B 2 ). It has three minable seams (C 1 , B 1 and B 2 ). The coal seam gas content in the Parvadeh coal deposit increased to a depth of 300 m with a value of 19 m 3 per ton and then it will be constant. In this deposit, the gas content of the surrounding rocks of the coal seam is 3-5 m 3 per ton at a depth of 500 m (Anon, 2005).
The Tabas coal mine is located in the Tabas coal region approximately 85 km south of Tabas in the South Khorasan province, Iran (see Figure 6). The C 1 seam which is located in the Tabas coal mine is mined by a mechanized longwall retreat mining method. The thickness and dip of the C 1 seam vary from 1.5 to 3 meters (approximately 2.2 m) and from 5 to 26 degrees, respectively. Intermittently low strength sandstone and siltstone layers form in the hangingwall of the coal seam. The distance between the C 1 seam and C 2 is approximately 12.9 m. The footwall consists of siltstone and mudstone seams (see Figure 7). The orientation of the major cleat set in respect to the C 1 coal seam direction is almost vertical. The direction of one of the sub set of cleats in relation to the C 1 seam direction is approximately parallel but with a plan plunge difference of 35 degrees relating to the horizon. The direction of the other is entirely parallel in relation to the C 1 coal seam direction (Shahriar et al., 2009).
In this mine, a three-entry system was used for serving a 220 m long longwall face. There are two rows of chain pillars between two adjacent panels. ure 7, the B 1 and B 2 coal seams are located above and below the C 1 coal seam and predicted after coal extraction the amount of gas entered to the mine working panel. Considering the high value of C 1 gas content, a horizontal methane drainage wellbore was designed for this mine and its implementation was planned for a depth greater than 300 m (Anon, 2005).
This paper concerns the panel at a depth of 300 m. The information of the Tabas coal mine for methane drainage classification is shown in Table 3.

Determination CMD index for the Tabas coal mine
For the determination of the coal seam methane drainageability index in the Tabas coal mine with the FRES method, the first step is the creation of an interaction matrix. For this purpose, by applying the arbitrations of specialists to the fuzzy system and using fuzzy rules on their views, the fuzzy interaction matrix was created and is shown in Table 4.
The second step consists of plotting a cause-effect diagram in order to identify dominant or subordinate parameters, and also interactive parameters. The parameter interaction intensity of each parameter is calculated according to Figure 8.
The C-E diagram of the affecting parameters on coal seam methane drainageability is plotted in Figure 9. The spots below the C=E line are called dominant and the spots above the C=E line are called subordinate. Conforming to this figure, along the C=E, the C+E value increases.
It can be seen that gas content (P 6 ) is mostly a subordinate parameter (affected by the system). The more interactive parameter is the permeability of coal (P 3 ) and the less interactive parameter is ash content (P 5 ). The most dominate parameter is coal seam depth (P 9 ).
The interaction intensity histogram (E+C) for each parameter is shown in Figure 10. This histogram displays that small changes in the parameters P 3 (Permeability of Coal), P 6 (Gas Content) and P 10 (In-situ stress)   have a great effect in the system treatment. These parameters have a maximum value of C+E in the system. Base on the weight value (see Table 5) of each parameter, the coal seam methane drainageability index (CMDI) is calculated. The coal seam methane drainageability index is an expression of the inherent potential methane drainage of the coal seam, where the maximum value of the index is 100 and refers to very good conditions for pre-drainage techniques in a working mine. The classification of methane drainageability status for a coal seam is shown in Figure 11. CMDI ranges between 0 and 100; CMDI <20 indicates very bad conditions for  <CMDI <80 corresponds to good conditions for methane drainage and 80 <CMDI <100 corresponds to very good conditions for methane drainage. It should be noted that by increasing the CMDI, the potential of methane drainage from a working mine increases. Therefore, it is recommended that for CMDI values between 60 and 80, horizontal boreholes and gob gas ventholes be implemented and for CMDI values between 80 and 100, vertical boreholes and gob gas ventholes be implemented. In this study, the CMDI value for the Tabas coal mine is 67.4. This value indicates the methane drainage method could be implanted in this mine. In summary, the flow sheet for determining the coal seam methane drainageability by FRES is presented in Figure 12.

Conclusion
In this study, a new approach, namely, coal seam methane drainageability index (CMDI) is developed for the classification of coal seam methane draingeability. In this study, after initial studies, the most important parameters (17 parameters) affecting methane drainage were selected. In the CMDI approach, the classification of a coal seam is based on the fuzzy rock engineering system. Accordingly, the first step is creating an interaction matrix by applying the fuzzy system to judgments of experts and using fuzzy rules on their views. Then a cause-effect diagram is plotted using the values of cause and effect parameters. By calculating the coefficient values of each parameter and performing a summation of the multiplication of them to assigned values for each input parameter, the coal seam methane draingeability index is calculated. According to this new approach, the following conclusions have been made: • The effect of each parameter on methane drainage from the coal seam in a working mine is evaluated. The results obtained from a cause-effect diagram show that the permeability of coal (P 3 ) is the most interactive parameter. In other words, a small change in this parameter causes a large change in the system. The most dominant parameter is coal seam depth (P 9 ) and the most subordinate parameter is gas content (P 6 ). • The application of this new approach at the Tabas coal mine for the classification C 1 coal seam showed that the C 1 coal seam is located in a good zone for methane drainage. The presented index based on the fuzzy RES is a suitable method which provides a reliable result for the prediction coal seam methane drainageability. However, such a proposed index usually requires future research for incorporating other parameters which may be critical for methane drainage from a coal seam. It should be noted that the present index is suitable for pre-drainage in a working mine, and is not necessarily appropriate for post-drainage techniques.