重磁(梯度)张量数据边界识别方法研究  

Investigation about edge recognition using(gradient)tensor data of magnetic and gravity

作　　者：赵建宇 明彦伯 孙成城 张志东 刘晓甲 

机构地区：[1]吉林大学地球探测科学与技术学院,长春130021

出　　处：《物探化探计算技术》2017年第6期748-754,共7页Computing Techniques For Geophysical and Geochemical Exploration

基　　金：国家重点研发项目(2016YFC0600505)

摘　　要：边界识别是重力数据解释的常规任务之一,但地质体的边界不能很好地与重力原始异常数据对应,而与重磁异常水平导数极大值、垂直导数零值相对应,因此大多利用该性质完成重磁边界识别任务。研究发现,现有边界识别方法会出现虚假边界,针对现有边界识别方法进行总结,并针对多余边界问题进行改进,提出新的边界识别,通过模型试验和实际数据证明,该方法可有效地去除多余边界,且降低了噪声的干扰,为重磁数据边界识别方法提供新的思路。The boundary identitication is one of the regular tasks of gravity and magnetic raw anomaly data does not well correspond to the boundary of geological bodyzontal derivative of gravity and magnetic anomalies are corresponding to the zero value of mostly to complete the assignment of gravity and magnetic boundary identitication. We tind that false bounsing current boundary identification method. This article summarizes the current boundary identification method and correctsthe problem of excessive boundaries to present new boundary dentification method. This new method can effectively removeexcessive boundaries and reduces the disturbance of noise , which provides a new thinking way for gravity and magnetic databoundary dentification method.

关 键 词：边界识别 重磁(梯度)张量数据 重磁勘探 

分 类 号：P631.2[天文地球—地质矿产勘探]