摘要
小断层及裂缝发育带对于油田提高抽采率和煤田的安全生产有着重要的影响,预测小断层及裂缝发育带已成为地球物理学中的重点内容。通过对相干、边缘检测、曲率和蚂蚁体等地震属性的研究,明确了地震属性对于构造成因的小断层及裂缝发育带有着极好的识别能力。同时,分析了以多属性直接叠合、多属性融合和有监督的神经网络运算为代表的多属性联合技术,发现其在小断层及裂缝发育带预测中有着较好的实用性。
Small faults and fracture-developed zones play an important role in improving the extraction rate in oil fields and the safe production in coal mines, so the prediction of small faults and fracture-developed zones has become the key content in geophysics. Through the study of the seismic attributes such as the coherency, edge detection, curvature and ant-body, it has been clear about that the seismic attributes have good ability to recognize tectonic genesis of small faults and fracture-developed zones. At the same time, analysis was made on the multi-attribute united technology such as multiple attribute composite, multiple attribute fusion and supervised neural network algorithm, it was found that the multi-attribute united technology has a good practicability in the prediction of small faults and fracture-developed zones.
出处
《矿业安全与环保》
北大核心
2014年第2期32-34,40,共4页
Mining Safety & Environmental Protection
关键词
小断层
裂缝发育带
地震属性
small fault
fracture-developed zone
seismic attribute
作者简介
宋劲（1974-），男，四川乐山人，博士研究生，高级工程师，现从事与矿山安全技术相关的开发和研究工作。E-mail：songjin33@163．com。
