【摘要】 以瓦斯地质基本理论为基础,利用地质和钻井数据建立了含瓦斯煤层的地质和地球物理模型.对所建立的地球物理模型,通过有限差分正演模拟方法获得了正演地震剖面.通过对地震剖面煤层反射波的属性分析,获得了相应的地震属性,在此基础上,运用支持向量机(SVM)方法对瓦斯突出危险区进行了预测.结果表明:运用惩罚参数C=32,γ=78.125×10-4的RBF核函数和所建模型对测试样本钻孔数据进行分类预测,预测精度为80%;对随机选择的训练样本数据进行回代预测,预测精度达到90%,为利用叠后地震数据预测瓦斯突出危险区提供了一条新途径.更多还原

【Abstract】 Based on coal gas theory,geological and geophysical models of gaseous coal seam were built by geological and drilling data.For the established models,forward modeling seismic sections were achieved by the computation of finite difference.By analysis of the coal reflection attributes of those modeling sections,seismic attributes were obtained.The SVM(Support Vector Machine) method was also used in our work to predict gas outburst risk area based on the extracted seismic attributes.The results show reveals that: firstly,the prediction accuracy is 80% in classifying and predicting drilling data of testing samples by using RBF kernel function with parameters C=32 and γ=78.125×10-4 and the established model;secondly,the prediction accuracy is as high as 90% when the prediction of randomly-selected training sample data is carried out recursively.This has provided a new approach to predict gas outburst risk area by using post-stack seismic data.更多还原