摘要
利用重力梯度张量数据高精度的特点以及解析信号在确定异常体位置上的优势,将重力梯度张量解析信号代替位场的导数完成重力梯度张量解析信号的欧拉反褶积;通过在1个窗口内对1组数据点解3个欧拉方程来自动识别构造指数,从而规避了传统欧拉反褶积方法中需要事先确定构造指数的问题,同时减少了背景场的影响。研究结果表明:使用重力梯度张量的解析信号,其欧拉反褶积的解收敛性很好,能准确地判断地下异常体源的位置,有效规避背景场的影响,反演效果较好。
Depending on high resolution of gravity gradient tensor data as well as the advantage of determining the location of gravity anomalies by the analytic signal, Euler deconvolution of the analytic signal of gravity gradient tensor was solved by analytic signal instead of gravity field derivatives. Structural index was automatically identified by a set of data points in a window solving Euler equations, so there was no need to determine structural index in advance and denoise background field which traditional Euler deconvolution method had. The results show that Euler deconvolution solution converges quickly, the disturbance of background field can be eliminated effectively, and the results of this method are useful and robust.
出处
《中南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2015年第1期217-222,共6页
Journal of Central South University:Science and Technology
基金
国家自然科学基金项目资助(41174061)~~
关键词
重力梯度张量
解析信号
欧拉反褶积
gravity gradient tensor
analytic signal
Euler deconvolution
