• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Geophysical Prospecting >Three-dimensional inversion of full magnetic gradient tensor data based on hybrid regularization method
【24h】

Three-dimensional inversion of full magnetic gradient tensor data based on hybrid regularization method

机译：基于混合正则化方法的全磁梯度张量数据的三维反演

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Rapid developments in SQUID-based technology make it possible for geophysical exploration to direct measure, inverse and interpret magnetic gradient tensor data. This contribution introduces a novel three-dimensional hybrid regularization method for inversion of magnetic gradient tensor data, which is based on the minimum support functional and total variation functional. Compared to the existing stabilizers, for example, the minimum support stabilizer, the minimum gradient support stabilizer or the total variation stabilizer, our proposed hybrid stabilizer, in association with boundary penalization, improves the revision result greatly, including higher spatial and depth resolution, more clear boundaries, more highlighted images and more evident structure depiction. Moreover, suitable selection of model parameter lambda will further improve the image quality of the recovered model. We verify our proposed hybrid method with various synthetic magnetic models. Experiment results prove that this method gives more accurate results, exhibiting advantages of less computational costs even when less prior information of magnetic sources are provided. Comparison of results with different types of magnetic data with and without remanence indicates that our inversion algorithm can obtain more detailed information on the source structure based on rational estimation of total magnetization direction. Finally, we present a case study for inverting SQUID-based magnetic tensor data acquired at Da Hinggan Mountains area, inner Mongolia, China. The result also certifies that the method is reliable and efficient for real cases.
机译：基于SQUID的技术的飞速发展使得地球物理勘探能够直接测量，反演和解释磁梯度张量数据。该贡献介绍了一种新颖的三维混合正则化方法，用于基于最小支持函数和总变化函数的磁梯度张量数据反演。与现有的稳定器相比，例如最小支持稳定器，最小梯度支持稳定器或总变化稳定器，我们提出的混合稳定器结合边界惩罚，极大地改善了修正结果，包括更高的空间和深度分辨率，更多清晰的边界，更突出的图像和更明显的结构描绘。此外，适当选择模型参数λ将进一步改善恢复模型的图像质量。我们用各种合成磁模型验证了我们提出的混合方法。实验结果证明，该方法给出的结果更准确，即使在提供较少的先验信息的情况下，仍具有计算成本低的优点。比较具有和没有剩磁的不同类型磁数据的结果，表明我们的反演算法可以基于对总磁化方向的合理估计来获得有关源结构的更多详细信息。最后，我们提供了一个案例研究，用于反转在中国内蒙古大兴安岭地区获得的基于SQUID的磁张量数据。结果还证明该方法对于实际情况是可靠且有效的。

著录项

  • 来源
    《Geophysical Prospecting》 |2019年第1期|226-261|共36页
  • 作者

    Ji Shuangxi; Zhang Huai; Wang Yanfei; Rong Liangliang; Shi Yaolin; Chen Yongshun;

  • 作者单位

    Chinese Acad Sci, Inst Geol & Geophys, Key Lab Petr Resources Res, Beijing 100029, Peoples R China;

    Peking Univ, Sch Earth & Space Sci, Dept Geophys, Beijing 100871, Peoples R China;

    Qingdao Natl Lab Marine Sci & Technol, Lab Marine Mineral Resources, Qingdao 266237, Peoples R China;

    Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China;

    Southern Univ Sci & Technol, Dept Ocean Sci & Engn, Shenzhen 518055, Peoples R China;

    Chinese Acad Sci, Shanghai Inst Microsyst & Informat, CAS Ctr Excellence Superconducting Elect, Shanghai 200050, Peoples R China;

    Univ Chinese Acad Sci, Key Lab Computat Geodynam, Beijing 100049, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Full magnetic gradient tensor data; Hybrid parameter regularization; Minimum support functional; MSTV stabilizer; TV regularization;

    机译：全磁梯度张量数据;混合参数正则化;最小支持功能;MSTV稳定器;TV正则化;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号