Abstract

During UCG operations, evaluation of the coal combustion cavity growth and precise control of the reactor are important to ensure effective combustion and efficient gasification. Enlargement of the oxidation surface around the gasification channel with crack initiation and development inside the coal seam directly influence the gasification efficiency.

To investigate the distribution and extent of fracture activity, and to evaluate the propagation of the combustion area in the UCG model experiments and small-scale field tests, we used acoustic emissions (AE) monitoring and temperature measurements. In this work, the AE signals from sensors CH1–CH6/CH8 were monitored and stored: the arrival time, number of events, and peak amplitude. The AE source locations and moment tensor analysis were investigated to establish a crack distribution model. With the monitoring results of temperature changes and AE activity, results showed coal fracture generation and extension in the gasifier. Results also showed that many AE events occurred during coal combustion. The AE activity was related closely to the temperature change occurring inside the coal. This AE generation apparently results from crack initiation and extension around the coal combustion area, which occur because of thermal stress. Moreover, coal consumption was investigated by calculating the cavity volumes formed in the gasifiers, and by estimating the reaction process of coal gasification based on the stoichiometry using product gas compositions. Results from the estimated values of coal consumption support experimental observations for the rational error range (about 15%) and provide a better evaluation of UCG effects.

Results show that the local temperature change strongly affects AE activities when fracture occurs inside the coal. A crack distribution model constructed with AE data is useful to evaluate the gasification process. It provides necessary data and parameters for UCG simulation development. The AE techniques are reliable for application to the real-time process control in UCG trials.

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