首页 | 本学科首页   官方微博 | 高级检索  
     检索      

应用低频信号提高高速玄武岩下的成像质量
引用本文:佘德平,管路平,徐颖,李佩.应用低频信号提高高速玄武岩下的成像质量[J].应用地球物理,2006,3(2):112-119.
作者姓名:佘德平  管路平  徐颖  李佩
作者单位:[1]Civil Engineering Department, Hehai University, Nanjing 210098, China [2]Nanjing Institute of Geophysical Prospecting of Sinopec Petroleum Exploration & Development Research Institute, Nanjing 210014, China
摘    要:针对高速玄武岩屏蔽层下深层成像困难的实际问题,采用波动方程波场数值模拟技术,根据玄武岩地层的特点,设计三个相应的简单高速玄武岩模型,通过对深层反射地震信号能量的分析,说明了低频地震信号既具有较强的穿透薄高速玄武岩屏蔽层的能力,也具有减弱因粗糙表面所产生的绕射噪音的能力。一个完整的2D玄武岩模型的模拟试验证明了利用低频信号可以提高高速玄武岩屏蔽层下深层成像的质量,实际资料的低通滤波处理也取得了预期的效果。

关 键 词:高速屏蔽层  玄武岩  低频信号  穿透力  成像  数值模拟
收稿时间:2006-04-30
修稿时间:2006-04-302006-05-18

Use of low-frequency signals to improve imaging quality under high-velocity basalt
Deping She,Luping Guan,Ying Xu,Pei Li.Use of low-frequency signals to improve imaging quality under high-velocity basalt[J].Applied Geophysics,2006,3(2):112-119.
Authors:Deping She  Luping Guan  Ying Xu  Pei Li
Institution:(1) Civil Engineering Department, Hehai University, Nanjing, 210098, China;(2) Nanjing Institute of Geophysical Prospecting of Sinopec Petroleum Exploration & Development Research Institute, Nanjing, 210014, China
Abstract:Wave equation wave field numerical modeling technology is applied to the observation that deep layer imaging is difficult below a screening layer of high-velocity basalt. Three simple high-velocity basalt models are designed on the basis of basalt formation characteristics. The analysis of deep-layer reflection seismic signal energy shows that low- frequency seismic signals are capable of both penetrating the thin high-velocity basalt layer and reducing the diffraction noise caused by the rough surfaces. The simulation experiment of a complete 2D basalt model confirms that the low-frequency signals can be used to boost the quality of deep-layer imaging under the high-velocity basalt layer and achieve good results in low-pass filter processing of actual data.
Keywords:high-velocity screening layer  basalt  low-frequency  penetrating force  and numerical modeling  
本文献已被 CNKI 维普 万方数据 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号