Prediction of Gas Emission quantity based on gas content uncertainty in coal mines

Prediction of gas emission before mining is difficult since it depends on a number of geology, geographical, and operation factor. The gas content is among the most important parameters for the assessment of gas emission through the coal layer both during and after the mining operation. The most important objective followed by studying the gas content is to evaluate the volume of gas that will emit upon extracting the coal from different depths, as it comprises a fundamental basis for the calculation of the required air volume for ventilating the coal mine. The large amounts of gas released during mining present concerns about sufficient airflow for ventilation to ensure worker safety. Hence, the functions of mine ventilation system are vital for an underground mining system. In the present study, the central data from a total of 64 exploratory boreholes was utilized. Once finished with identifying the most important coal layers in terms of gas emission, the variogram modeling as performed to define the distribution of the gas content across the coal layer. Subsequently, simulations were performed to stochastically assess the gas content. So, an approach is provided for the prediction of gas emission based on a random simulation method, Monte-Carlo Simulation (MCS). For this purpose, six factors are selected for predicting methane emissions including main layer gas content, main layer thickness, advanced rate, production rate, adjacent layer gas content, adjacent layer thickness and main layer distance from adjacent layers. The result shows that the prediction model has enough prediction accuracy for application of actual engineering in the coal mine. The predicted value is also essentially consistent with the actual value and the prediction method based on the uncertainty theory is reliable.