Guidelines for the prediction and control of methane emissions on longwalls

"Although longwall mining productivity can far exceed that of room-and-pillar mining, the total methane emissions per extracted volume associated with longwall sections are generally higher than those for continuous miner or pillar removal sections. Increased face advance rates, increased productivities, increased panel sizes, and more extensive gate road developments have challenged existing designs for controlling methane on longwalls. Methane control research by the National Institute for Occupational Safety and Health (NIOSH) recently examined a number of practices designed to maintain concentrations in mine air within statutory limits and consistently below the lower explosive limit. In this report, several practical guidelines are recommended for controlling longwall coalbed methane. All predictions are based on determinations made for the Pittsburgh Coalbed in southwestern Pennsylvania."1. Reservoir modeling for predicting methane emissions in development headings (entries) -- 2. Controlling longwall face methane and development mining emissions: predicted improvements using in-seam boreholes -- 3. Characterizing and forecasting longwall face methane emission rates for longer longwall faces -- 4. Predicting methane emissions from longer longwall faces by analysis of emission -- contributors -- 5. Development of numerical models to investigate permeability changes, distributions, and gas emissions around a longwall panel -- 6. Methane emission control during mining of longwall panels using gob gas ventholes -- 7. The application of gob gas ventholes to control methane in wider longwall panels and gobs -- 8. Induced fracturing and coalbed gas migration in longwall panel overburden: the NIOSH borehole monitoring experiment6 -- Practical guidelines for controlling longwall coalbed methaneby Steven J. Schatzel, C. O?zgen Karacan, Robert B. Krog, Gabriel S. Esterhuizen, and Gerrit V. R. Goodman"March 2008."Also available via the World Wide Web as an Acrobat .pdf file (3.77 MB, 93 p.).Includes bibliographical references (p. 80-83)

Evaluation of the relative importance of coalbed reservoir parameters for prediction of methane in?ow rates during mining of longwall development entries

This study presents a reservoir modeling approach to investigate the relative effects of different coalbed parameters on the migration of methane into development entries. A base coalbed reservoir model of a three-entry development section, where grids were dynamically controlled to simulate the advance of mining at a constant section advance rate, was created and calibrated for a Pittsburgh Coalbed mine in the Southwestern Pennsylvania section of the Northern Appalachian Basin. The values of coalbed parameters were varied to evaluate their effects on predicted methane emissions for various development distances. The results of these parametric simulations were then used to derive linear expressions relating these parameters to methane emissions into the workings. These models were analyzed to assess their significance and adequacy for predictive purposes. This work shows that coupling reservoir simulations with linear modeling yield a technique that can be applicable to different coalbeds. The reservoir parameters used by the linear models (coalbed thickness, pressure, sorption time constant, Langmuir parameters, permeability) can be determined by running relatively simple laboratory tests, such as adsorption equilibrium and permeability determination, on coal samples obtained either from the mining operation or from the exploratory boreholes drilled ahead of mining.2008820

Numerical Analysis Of The Influence Of In-Seam Horizontal Methane Drainage Boreholes On Longwall Face Emission Rates

High methane emissions originating from the active face areas and from the fractured formations overlying and underlying the mined coalbed can adversely affect both safety and productivity in underground coal mines. Since ventilation alone may not be sufficient to control the methane levels in the longwall mining environment, gob gas ventholes have become a standard supplementary methane control option in many mines. As mines progress into deeper and gassier coalbeds, or as longwall panel size increases, ventilation and gob gas ventholes together may not be sufficient to maintain methane levels within statutory limits. To decrease the risk associated with methane emissions under these circumstances, in-seam horizontal methane drainage is often used to reduce the gas content of the coalbed prior to mining. Horizontal methane drainage borehole completion designs, drilling strategies, and degasification lead times may need to be adjusted for site-specific conditions due to mine design, geology, and the gas content of the coalbed. This study investigates different horizontal methane drainage borehole patterns, borehole lengths, and degasification times prior to and during panel extraction to evaluate their effectiveness in reducing methane emissions using a "dynamic" 3D reservoir modeling of a 38 1-m wide longwall panel operating in the Pittsburgh coalbed. Results of this study showed that dual and tri-lateral boreholes are more effective in decreasing emissions and in shielding the entries compared to fewer shorter, cross-panel, horizontal boreholes parallel to the longwall face. Modeling results showed that after 12 months of pre-mining methane drainage, the average longwall face emission rates can be reduced by as much as 10.3 m3/min and 6.8 m3/min using tri- and dual-lateral boreholes, respectively. It was also shown that if pre-mining methane drainage time is short, it is important to continue methane drainage during the panel extraction to maximize reductions in longwall face emissions since additional face emission reductions achieved during this period can be comparable to pre-mining degasification

Reservoir Engineering Considerations For Coal Seam Degasification And Methane Control In Underground Coal Mines

Degasification and methane control in underground coal mining is an important area augmenting conventional ventilation in order to prevent possible fires and explosions due to excessive methane emissions. Coal bed reservoir engineering has been applied for many years to coalbed methane production. In recent years, modeling the flow and draining methane, not only from coal bed itself but also from the overlying strata, have been recognized as important areas of expertise for supplementing underground ventilation. This paper demonstrates the applications of coal bed reservoir engineering and modeling techniques for optimizing and controlling methane emissions in longwall and continuous miner sections. Practical applications and some considerations are presented for reservoir modeling, borehole performances, and face emission predictions for various coal bed and borehole configurations. A section on field reservoir studies and well bore log analyses for methane control are also presented as a complementary way of controlling methane and optimizing ventilation.2009783

Forecasting gob gas venthole production performances using intelligent computing methods for optimum methane control in longwall coal mines

Gob gas ventholes (GGV) are used to control methane inflows into a longwall operation by capturing it within the overlying fractured strata before it enters the work environment. Thus, it is important to understand the effects of various factors, such as drilling parameters, location of borehole, applied vacuum by exhausters and mining/panel parameters in order to be able to evaluate the performance of GGVs and to predict their effectiveness in controlling methane emissions. However, a practical model for this purpose currently does not exist. In this paper, we analyzed the total gas flow rates and methane percentages from 10 GGVs located on three adjacent panels operated in Pittsburgh coalbed in Southwestern Pennsylvania section of Northern Appalachian basin. The ventholes were drilled from different surface elevations and were located at varying distances from the start-up ends of the panels and from the tailgate entries. Exhauster pressures, casing diameters, location of longwall face and mining rates and production data were also recorded. These data were incorporated into a multilayer-perceptron (MLP) type artificial neural network (ANN) to model venthole production. The results showed that the two-hidden layer model predicted total production and the methane content of the GGVs with more than 90% accuracy. The ANN model was further used to conduct sensitivity analyses about the mean of the input variables to determine the effect of each input variable on the predicted production performance of GGVs

Reconciling longwall gob gas reservoirs and venthole production performances using multiple rate drawdown well test analysis

Longwall mining is an underground mining method during which a mechanical shearer progressively mines a large block of coal, called a panel, in an extensive area. During this operation the roof of the coal seam is supported only temporarily with hydraulic supports that protect the workers and the equipment on the coal face. As the coal is extracted, the supports automatically advance and the roof strata cave behind the supports. Caving results in fracturing and relaxation of the overlying strata, which is called "gob." Due its highly fractured nature, gob contains many flow paths for gas migration. Thus, if the overlying strata contain gassy sandstones or sandstone channels, gas shales or thinner coal seams which are not suitable for mining, then the mining-induced changes can cause unexpected or uncontrolled gas migration into the underground workplace. Vertical gob gas ventholes (GGV) are drilled into each longwall panel to capture the methane within the overlying fractured strata before it enters the work environment. Thus, it is important, first to understand the properties of the gas reservoir created by mining disturbances and, second, to optimize the well parameters and placement accordingly. In this paper, the production rate-pressure behaviors of six GGVs drilled over three adjacent panels were analyzed by using conventional multi-rate drawdown analysis techniques. The analyses were performed for infinite acting and pseudo-steady state flow models, which may be applicable during panel mining (DM) and after mining (AM) production periods of GGVs. These phases were analyzed separately since the reservoir properties, due to dynamic subsidence, boundary conditions and gas capacity of the gob reservoir may change between these two stages. The results suggest that conventional well test analysis techniques can be applicable to highly complex gob reservoirs and GGVs to determine parameters such as skin, permeability, radius of investigation, flow efficiency and damage ratio. The insights obtained from well test analyses can be used for a better understanding of the gob and for designing more effective gob gas venthole systems.2009820

J Nat Gas Sci Eng

The Black Warrior Basin of Alabama is one of the most important coal mining and coalbed methane production areas in the United States. Methane control efforts through degasification that started almost 25 years ago for the sole purpose of ensuring mining safety resulted in more than 5000 coalbed methane wells distributed within various fields throughout the basin. The wells are completed mostly in the Pratt, Mary Lee, and Black Creek coal groups of the Upper Pottsville formation and present a unique opportunity to understand methane reservoir properties of these coals and to improve their degasification performances. The Brookwood and Oak Grove fields in the Black Warrior Basin are probably two of the most important fields in the basin due to current longwall coal mining activities. In this work, methane and water productions of 92 vertical wellbores drilled, some completed 20 years ago, over a current large coal mine district located in these two fields, were analyzed by history matching techniques. The boreholes were completed at the Mary Lee coal group, or at combinations of the Pratt, Mary Lee, and Black Creek groups. History matching models were prepared and performed according to properties of each coal group. Decline curve analyses showed that effective exponential decline rates of the wells were between 2% and 25% per year. Results of production history matching showed, although they varied by coal group, that pressure decreased as much as 80% to nearly 25 psi in some areas and resulted in corresponding decreases in methane content. Water saturation in coals decreased from 100% to between 20 and 80%, improving gas relative permeabilities to as much as 0.8. As a result of primary depletion, permeability of coal seams increased between 10 and 40% compared to their original permeability, which varied between 1 and 10 md depending on depth and coal seam. These results not only can be used for diagnostic and interpretation purposes, but can be used as parameter distributions in probabilistic simulations, as illustrated in the last section of this paper. They can also be used in conjunction with spatial modeling and geological considerations to calculate potential methane emissions in operating mines.YLH8/Intramural CDC HHS/United States2015-07-17T00:00:00Z26191096PMC450627

MULTISCALE MODELING OF THE MINE VENTILATION SYSTEM AND FLOW THROUGH THE GOB

The following dissertation introduces the hazard of methane buildup in the gob zone, a caved region behind a retreating longwall face. This region serves as a reservoir for methane that can bleed into the mine workings. As this methane mixes with air delivered to the longwall panel, explosive concentrations of methane will be reached. Computational fluid dynamics (CFD) is one of the many approaches to study the gob environment. Several studies in the past have researched this topic and a general approach has been developed that addresses much of the complexity of the problem. The topic of research herein presents an improvement to the method developed by others. This dissertation details a multi-scale approach that includes the entire mine ventilation network in the computational domain. This allows one to describe these transient, difficult to describe boundaries. The gob region was represented in a conventional CFD model using techniques consistent with past efforts. The boundary conditions, however, were cross coupled with a transient network model of the balance of the ventilation airways. This allows the simulation of complex, time dependent boundary conditions for the model of the gob, including the influence of the mine ventilation system (MVS). The scenario modeled in this dissertation was a property in south western Pennsylvania, working in the Pittsburgh seam. A calibrated ventilation model was available as a result of a ventilation survey and tracer gas study conducted by NIOSH. The permeability distribution within the gob was based upon FLAC3d modeling results drawn from the literature. Using the multi-scale approach, a total of 22 kilometers of entryway were included in the computational domain, in addition to the three dimensional model of the gob. The steady state solution to the problem, modeling using this multi-scale approach, was validated against the results from the calibrated ventilation model. Close agreement between the two models was observed, with an average percent difference of less than two percent observed at points scattered throughout the MVS. Transient scenarios, including roof falls at key points in the MVS, were modeling to illustrate the impact on the gob environment

DEVELOPMENT OF UNIVARIATE AND MULTIVARIATE FORECASTING MODELS FOR METHANE GAS EMISSIONS IN UNDERGROUND COAL MINES

Methane gas management continues to be a challenge concerning underground coal mine safety and productivity worldwide despite the extraordinary effort of the mining industry, governmental agencies, and academia to develop new technologies to monitor and control methane gas emissions more efficiently. The risk of hazardous methane gas concentrations in underground environments cannot be underestimated. Statistical data for the last 100 years indicate that around 80% of the accidents and 90% of the fatalities in the underground coal mining industry in the US were related to methane gas explosions. Modern underground mine operations monitor and evaluate atmospheric parameters such as barometric pressure, temperature, gas concentrations, and ventilation parameters (e.g., fan performance and airflow) by means of Automated Atmospheric Monitoring Systems, which use sensors that collect a massive amount of data implemented by mine operators to make decisions concerning mine safety and operate ventilation systems more effectively. In addition, however, some of these data can be statistically studied to develop forecast models to help improve the safety and health parameters of underground coal mining operations. The research presented in this dissertation investigates potential correlations between methane gas concentrations and independent variables such as barometric pressure and coal production rate to build reliable forecasting models capable of predicting future concentrations of methane gas, mainly based on time series data collected by the Atmospheric Monitoring System of three active underground coal mining operations in the eastern US and weather data retrieved from public weather stations in the proximity of the case studies. The mine and weather data were stored and pre-processed using an Atmospheric Monitoring Analysis and Database Management system explicitly designed to manage Atmospheric Monitoring Systems data. Furthermore, various statistical techniques were implemented to assess the potential association (e.g., autocorrelation and cross-correlation) between methane gas concentration time series and the independent variables. Such associations were employed to develop univariate and multivariate forecasting models for methane gas emissions in underground coal mines. Finally, the optimal model is selected using the Akaike Information Criterion, and the results obtained from the different forecast approaches (univariate and multivariate) are compared using cross-validation metrics to determine the best model. It was concluded that the ARIMA, VAR, and ARIMAX methane gas forecasting methodologies proposed in this research can accurately predict methane gas concentrations in underground coal mines operations. The methane gas forecasted from the models matched the validation data consistently, and their linear correlation was positive and strong in most cases. In addition, the 95% confidence interval consistently captured the forecast and validation data