中文摘要：

山西国阳新能股份有限公司新景煤矿3煤层在掘进和回采过程中，频发煤与瓦斯突出事故，给煤矿安全生产带来隐患．通过多个采区的瓦斯地质调查，发现大部分区域的瓦斯突出与煤层的顶板岩性（砂岩）和煤层结构（煤层的冲刷变薄）密切相关，当3煤层被顶板砂岩冲刷变薄，即3煤层顶板砂岩的厚度增加时，极易发生瓦斯突出．本文对研究区的测井曲线进行特征分析，并对测井曲线进行融合处理，利用多参数岩性反演的方法获得的波阻抗数据体可以对3煤层顶板砂岩的分布特征进行详细研究．反演结果与实际情况吻合度较高，且在瓦斯突出点位置，煤层顶板的波阻抗值明显增大，并能够清晰地辨别砂岩的位置和空间形态，其研究成果对新景煤矿瓦斯预测和治理具有重要意义．

英文摘要：

Gas outburst occasions often happen in coalbed No. 3 during the process of tunneling and extraction of Xinjing coalmine, Guo Yang New Energy Incorporated Company, bringing potential safety risk to mining exploit. According to the researches of gas geological principles from different mining districts, it seems very common that the gas problem is closely related to the eoalbed roof lithology, sandstone and coal body structures, washed and destructed by the sandstone. In other words, the thicker the roof sandstone is , the thinner the coal is, and the more potential of the phenomenon of coal washing by the roof sandstone, which increases the possibility of gas outburst. Using seismic inversion to deeply detect the lithological change is one of the best options, which combines seismic data and log curve to improve the resolution of the earth underground. Usually, density and P-wave are considered when it comes to conventional impedance inversion, which has no effective impact when the density or P-wave has no great changes between the target layer and the other lithology. In this paper, well log curves in this area have been analyzed, in order to integrate these anomalies from two different curves into one curve that has both characteristics that reflect sandstone and coal at the same time, which considers multiple parameters of the target layer in order toidentify it from other lithology. Using this integrated curve, multi-parameter lithological seismic inversion method has been applied to achieving the impedance data, which can be utilized to identify the spatial structure and lithological range of the roof sandstone. With this method applied to a real mining district of Xinjing Coalmine, the inverted results are highly consistent with actual well data, which indicates that the method is effective and efficient which is of great value in gas prediction and management.