Study Of Soil Radon Concentration Variation On Coal Gasification Surface

Underground coal gasification(UCG) is a new comprehensive energy production and development technology, which can underground gasify abandoned and unrecoverable and uneconomical coal resource into gas, for civil and industrial use.At present, China is in a stage of energy structure adjustment, the way of energy production and energy utilization must have higher requirements. Compared with the traditional way of coal mining utilizing, underground coal gasification have clear advantages in environmental protection, energy development and utilization,economic efficiency, safety and other aspects. With the continuous development of Chinese coal gasification technology, underground coal gasification have gradually from laboratory research transformed to commercial production. However, the main bottlenecks problems in commercial production are the instability of produced combustible gas concentration, composition and calorific value. To solve this problem it needs to achieve effective monitoring of the state of underground coal combustion, in order to control the coal combustion process, which is a major difficulty in underground gasification.Based on the national science foundation project, the research of underground gasification furnace temperature field acquiring method through soil radon measurement technique in coal, radioactive radon measurement was applied to monitor the combustion states of coal gasification underground at coal gasification test area in Inner Mongolia. Using traditional statistical methods, trend surface analysis and wavelet analysis to research the distribution characteristics of radon concentration at the gasification test area in different gasification process, the results show that the distribution of the radon anomaly delineated by three methods has a certain relationship with the temperature underground combustion zone. Among these methods, the distribution and tendency of the radon anomaly delineated by the trend surface analysis have a good agreement with the distribution and tendency of temperature field in underground combustion zone, and has a better effect on delineating the underground combustion zone.Surface soil radon concentration changed with the external factors(temperature,humidity, etc.). Therefore, soil radon concentration daily variation and its main influencing factors were researched in coal gasification test area respectively under the original conditions and gasification furnace combustion state combined with correlation analysis and regression analysis, analysis of the variation law of soil radon concentration and its main influencing factors from different meteorological conditions. The research showed that either the state radon concentration variation or the dominant influence factor was different under the conditions of different meteorological, and surface soil temperature had a significant change. When soil moisture was low with little change in the original conditions, the difference of air temperature and soil temperature caused by the lag of the soil temperature became the main factor of the diurnal variation of the soil radon concentration, which caused The abnormal changes of soil radon concentration and the negative correlation between the soil temperature and the concentration of radon; In the gasification furnace combustion conditions, the soil radon concentration is high in the morning and low at noon, the dominant factors were the air temperature and soil humidity;While under the condition of continuous rain, soil temperature was the dominant factors of soil radon concentration variation. In general, the diurnal variation of soil radon concentration was the result of the common action of all kinds of influencing factors, and the leading factor was the key factor to cause the change of soil radon concentration.Acquired the underground coal gasification combustion temperature had an important role for monitoring the underground coal combustion state. Studied using the neural network and principal component analysis to establish neural network model of underground temperature field, which could be correspond to the multi-parameter soil radon measurements. To verify the feasibility of neural network model of underground temperature field by establishing the multi-parameter soil radon neural network model. Studies showed that the combination of principal component analysis to extract relevant feature quantity, the multi-parameter soil radon neural network model is effective. In addition, the neural network reflected the high sensitivity to the training sample, if the training samples were more representative, the multi-parameter neural network of underground gasification temperature field model was also feasible and effective, which could get the underground coal gasification temperature corresponding to the soil radon measurements under different parameters, it had a great significance for monitoringthe underground coal gas state.