摘要
由于地表电阻率法受到浅地表局部异常体的干扰,反演精度受到影响,井中装置数据资料参与反演虽然可以减小浅地表局部异常体的干扰,但是由于钻井位置的局限性,数据量得不到保障,也会导致反演精度降低.为此,本文开发了一套结合地表、地-井、井-地和井-井装置数据的三维联合反演算法.首先,利用有限差分法实现正演模拟,采用非线性共轭梯度法(NLCG)恢复电阻率结构;其次,调用Message Passing Interface(MPI)函数库加速正演模拟和灵敏度矩阵运算,当开辟12个进程时,反演程序获得最大加速比4.51;最后,通过合成数据和实测数据算例证明该反演算法的有效性,也证实了多种装置组合数据体反演结果明显优于单一地表装置数据体反演结果.
Because of interference from local anomaly bodies in the shallow subsurface,the inversion accuracy of ground-based resistivity method is limited.Although such interference can be reduced by virtue of borehole data in the inversion,due to the limitation of drilling position,the amount of data is not guaranteed,thus precision of inversion can be reduced.In this paper,a set of three-dimensional joint inversion algorithms that can simultaneously invert surface,surface-borehole,borehole-surface and borehole-borehole array data is developed.Firstly,forward modeling is conducted by the finite different method,and restoration of the resistivity structure is made by the Nonlinear Conjugate Gradient method(NLCG).Secondly,the Message Passing Interface(MPI)function library is used to accelerate forward modeling and sensitivity matrix calculation.The maximum speedup ratio of 4.51 is achieved by the inversion program when the 12 processes are opened up.Finally,the validity of the inversion algorithm is proved by numerical examples of synthetic data and measured data,and it is also proved that the inversion results of the combined data set of multiple arrays are obviously superior to those of a single surface array data set.
作者
马欢
郭越
吴萍萍
谭捍东
MA Huan;GUO Yue;WU PingPing;TAN HanDong(School of Earth Sciences,Institute Disaster of Prevention Science and Technology,Hebei Sanhe 065201,China;School of Electronic Science and Control Engineering,Institute Disaster of Prevention Science and Technology, Hebei Sanhe 065201,China;School of Geophysics and Information Technology,China University of Geosciences,Beijing 100083,China)
出处
《地球物理学报》
SCIE
EI
CAS
CSCD
北大核心
2018年第12期5052-5065,共14页
Chinese Journal of Geophysics
基金
国家自然科学基金(41804119
41704055)
中央高校基本科研业务费资助计划项目(ZY20180205)联合资助
