吉林大学学报(地球科学版) ›› 2021, Vol. 51 ›› Issue (2): 543-551.doi: 10.13278/j.cnki.jjuese.20200169

• 地球探测与信息技术 • 上一篇    下一篇

三维重力梯度局部光滑约束反演

罗永超, 李桐林, 张镕哲   

  1. 吉林大学地球探测科学与技术学院, 长春 130026
  • 收稿日期:2020-07-21 出版日期:2021-03-26 发布日期:2021-04-06
  • 通讯作者: 李桐林(1962-),男,教授,博士生导师,主要从事地球物理数据的处理与解释方面的研究,E-mail:1612935037@qq.com E-mail:1612935037@qq.com
  • 作者简介:罗永超(1995-),男,硕士研究生,主要从事重力及其梯度数据的处理与解释方面的研究,E-mail:593727741@qq.com
  • 基金资助:
    国家重点研发计划项目(2017YFC0601606);中国博士后科学基金特别资助(站前)项目(2020TQ0114);中国博士后科学基金项目(2020M681036)

Local Smooth Inversion of 3D Gravity Gradient

Luo Yongchao, Li Tonglin, Zhang Rongzhe   

  1. College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China
  • Received:2020-07-21 Online:2021-03-26 Published:2021-04-06
  • Supported by:
    Supported by the National Key Research and Development Project (2017YFC0601606),the China Post-Doctoral Science Foundation Special Grants (Pre-Station) Projects (2020TQ0114) and the Project Funded by China Postdoctoral Science Foundation (2020M681036)

摘要: 针对重力勘探中光滑反演存在的分辨率较低的问题,本文提出一种基于地质体埋深、地层倾向等一定先验信息的局部光滑约束三维反演算法,并提出了一种光滑反演中粗糙度矩阵的存储方式,该存储方式可以将M×N维粗糙度矩阵存储为M×2维,减少了计算机计算内存,且详细介绍了该存储方式下粗糙度矩阵与其他矩阵相乘时,粗糙度矩阵所存储的位置信息的读取方式以及与其他矩阵逐列逐步相乘最终得到计算结果的过程。最后,利用文中提出的算法对理论模型和实测数据进行反演试算,结果表明局部光滑反演算法相比于全局光滑反演结果更加准确,且该算法在一定噪声水平下依然稳定,在实际生产中有效可行。

关键词: 重力梯度, 粗糙度矩阵存储, 局部光滑约束, 反演

Abstract: Aiming at the low resolution problem of smooth inversion in gravity exploration, the authors proposed a local smooth constrained three-dimensional inversion algorithm based on certain prior information such as the depth of geological bodies and stratum inclination, and a storage method of roughness matrix in smooth inversion. By this method the computer's calculation memory can be reduced through storing the M×N dimension roughness matrix as M×2 dimension, and when the roughness matrix is multiplied by other matrices in this storage mode, the position information stored in the roughness matrix can be read,and the calculating results can be obtained. The theoretical model and measured data were used to perform inversion trial calculations using the algorithm proposed in this study. It is shown that the result of the local smooth inversion algorithm is more accurate than the result of the global smooth inversion, and the algorithm is still stable,effective,and feasible under a given noise level in production.

Key words: gravity gradient, roughness matrix storage, partial smooth constraint, inversion

中图分类号: 

  • P631.1
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