3D electromagnetic imaging using a new parallel GILD nonlinear inversion

1997 ◽  
Author(s):  
Ganquan Xie ◽  
Jianhua Li ◽  
Daxin Zuo
Keyword(s):  
Nonlinear Inversion ◽  
Electromagnetic Imaging

A nonlinear inversion method for 3D electromagnetic imaging using adjoint fields

1999 ◽  
Vol 15 (6) ◽  
pp. 1523-1558 ◽  
Author(s):  
O Dorn ◽  
H Bertete-Aguirre ◽  
J G Berryman ◽  
G C Papanicolaou
Keyword(s):  
Inversion Method ◽  
Nonlinear Inversion ◽  
Electromagnetic Imaging

Nonlinear Inversion

2009 ◽  
Author(s):  
Robert I. Odom
Keyword(s):  
Nonlinear Inversion

Unsupervised Algorithm for Brain Anomalies Localization in Electromagnetic Imaging

2020 ◽  
Vol 6 ◽  
pp. 1595-1606
Author(s):  
Aida Brankovic ◽  
Ali Zamani ◽  
Adnan Trakic ◽  
Konstanty Bialkowski ◽  
Beadaa Mohammed ◽  
...  
Keyword(s):  
Electromagnetic Imaging ◽  
Brain Anomalies

Subzone-based nonlinear inversion scheme for viscoelastic tissue properties

2000 ◽  
Author(s):  
Elijah E. W. Van Houten ◽  
Keith D. Paulsen ◽  
Michael I. Miga ◽  
Francis E. Kennedy ◽  
John B. Weaver
Keyword(s):  
Nonlinear Inversion ◽  
Tissue Properties

Improved Hybrid Particle Swarm Optimizer With Sine-Cosine Acceleration Coefficients For Transient Electromagnetic Inversion

2021 ◽  
Vol 16 ◽  
Author(s):  
Ruiheng Li ◽  
Qiong Zhuang ◽  
Nian Yu ◽  
Ruiyou Li ◽  
Huaiqing Zhang
Keyword(s):  
Learning Strategy ◽  
Particle Swarm ◽  
Population Diversity ◽  
Nonlinear Inversion ◽  
Test Functions ◽  
Particle Swarm Optimizer ◽  
Local Optima ◽  
Hybrid Particle ◽  
Transient Electromagnetic ◽  
Stability And Accuracy

Background: Recently, particle swarm optimization (PSO) has been increasingly used in geophysics due to its simple operation and fast convergence. Objective: However, PSO lacks population diversity and may fall to local optima. Hence, an improved hybrid particle swarm optimizer with sine-cosine acceleration coefficients (IH-PSO-SCAC) is proposed and successfully applied to test functions and in transient electromagnetic (TEM) nonlinear inversion. Method: A reverse learning strategy is applied to optimize population initialization. The sine-cosine acceleration coefficients are utilized for global convergence. Sine mapping is adopted to enhance population diversity during the search process. In addition, the mutation method is used to reduce the probability of premature convergence. Results: The application of IH-PSO-SCAC in the test functions and several simple layered models are demonstrated with satisfactory results in terms of data fit. Two inversions have been carried out to test our algorithm. The first model contains an underground low-resistivity anomaly body and the second model utilized measured data from a profile of the Xishan landslide in Sichuan Province. In both cases, resistivity profiles are obtained, and the inverse problem is solved for verification. Conclusion: The results show that the IH-PSO-SCAC algorithm is practical, can be effectively applied in TEM inversion and is superior to other representative algorithms in terms of stability and accuracy.

Borehole Casing Sources for Electromagnetic Imaging of Deep Formations

2014 ◽  
Author(s):  
Alberto Francesco Marsala ◽  
Andrew D. Hibbs ◽  
H. Frank Morrison
Keyword(s):  
Electromagnetic Imaging
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