Large scale roof strata caving that occurs during coal extraction can irreversibly damage floor strata and result in riskier mining operations. Four research models incorporating floor water pressure were assessed for floor strata failure, using eight methods and two classification systems. A connection between floor strata failure and the coefficient of impact risk was developed. The derived equations represent a potentially effective method for providing a preliminary assessment of the risks associated with floor strata failure due to caving. A classification system of floor failure potential can be constructed to minimize risks during mining.

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The total organic carbon content (TOC) is an important parameter for source rocks evaluation in coal measures. Total organic carbon content determined from logging parameters using back propagation neural network technique, which provide a new method for hydrocarbon source rock evaluation. Use the Turpan Basin Xishanyao formation as the research object. The five logs which consist of volume gamma logging (GR), acoustic logging (AC), density logging (DEN), resistivity logging (RT) and compensation neutron logging (CNL) were selected optimally based on the correlation analysis of the total organic carbon content measured data and well logging parameters as the input vector of BP neural network, and the total organic carbon content was selected as the output vector of BP neural network. Then the BP neural network model was established and applied to predict total organic carbon content for Xishanyao formation of B1 well in the Turpan Basin, with a competitive analysis of the prediction errors. The error between prediction values and measured values is small, and the majority of the relative errors are less than 8%. The results show that the BP neural network model based on logging with optimal parameters has a very strong generalization ability, and can approximate the nonlinear relationship between total organic carbon content and logging parameters of coal measure source rocks with high accuracy.

Abstract-In order to study the characteristics of heavy metals of the groundwater in the gangue-filled reclamation area, the heavy metals were investigated at Ju-Ji Coal mine with high groundwater level. The samples of the groundwater were gathered in the gangue-filled reclamation area at different time, studying the .characteristics of heavy metals of the groundwater. The results were as follows: the heavy metal content of the Cd, Hg, As and Pb increased with the increase of reclamation time. The heavy metal content of groundwater associated with the reclamation time in linear time.

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