scholarly journals Magnetotelluric and airborne magnetic data analysis to delineate subsurface structure in South-Eastern part of Korea

2019 ◽  
Author(s):  
Seong Kon Lee ◽  
Hyoungrae Rim ◽  
In Hwa Park ◽  
You Hong Kihm
Keyword(s):  
Data Analysis ◽  
Magnetic Data ◽  
Subsurface Structure ◽  
South Eastern ◽  
Airborne Magnetic

Installation and preliminary data analysis of Penang magnetic data Acquisition system (MAGDAS) in Malaysia

2021 ◽  
Vol 67 (7) ◽  
pp. 2199-2206
Author(s):  
N.A. Zakaria ◽  
S.H.M. Yusoff ◽  
N.A.M. Rizal ◽  
N.S.A. Hamid ◽  
M.H. Hashim ◽  
...  
Keyword(s):  
Data Analysis ◽  
Data Acquisition ◽  
Preliminary Data ◽  
Data Acquisition System ◽  
Acquisition System ◽  
Magnetic Data

Magnetic inversion to recover the subsurface block structures based on L1 norm and total variation regularization

2021 ◽  
Author(s):  
Mitsuru Utsugi
Keyword(s):  
Total Variation ◽  
Magnetic Data ◽  
Preconditioned Conjugate Gradient ◽  
Inversion Method ◽  
Total Variation Regularization ◽  
Subsurface Structure ◽  
L1 Norm ◽  
Magnetic Inversion ◽  
Original Definition ◽  
Primal Dual

Summary This paper presents a new sparse inversion method based on L1 norm regularization for 3D magnetic data. In isolation, L1 norm regularization yields model elements which are unconstrained by the input data to be exactly zero, leading to a sparse model with compact and focused structure. Here, we complement the L1 norm with a penalty minimizing total variation, the L1 norm of the model gradients; it is expected that the sharp boundaries of the subsurface structure are not compromised by incorporating this penalty. Although this penalty is widely used in the geophysical inversion studies, it is often replaced by an alternative quadratic penalty to ease solution of the penalized inversion problem; in this study, the original definition of the total variation, i.e., form of the L1 norm of the model gradients, is used. To solve the problem with this combined penalty of L1 norm and total variation, this study introduces alternative direction method of multipliers (ADMM), which is a primal-dual optimization algorithm that solves convex penalized problems based on the optimization of an augmented Lagrange function. To improve the computational efficiency of the algorithm to make this method applicable to large-scale magnetic inverse problems, this study applies matrix compression using the wavelet transform and the preconditioned conjugate gradient method. The inversion method is applied to both synthetic tests and real data, the synthetic tests demonstrate that, when subsurface structure is blocky, it can be reproduced almost perfectly.

Magnetic Data Acquisition System (MAGDAS) Malaysia: installation and preliminary data analysis at ESERI, UNISZA

2018 ◽  
Vol 93 (5) ◽  
pp. 553-564 ◽  
Author(s):  
R. Umar ◽  
◽  
S. F. Natasha ◽  
S. S. N. Aminah ◽  
K. N. Juhari ◽  
...  
Keyword(s):  
Data Analysis ◽  
Data Acquisition ◽  
Preliminary Data ◽  
Data Acquisition System ◽  
Acquisition System ◽  
Magnetic Data

Corrections for Altitude Fluctuations in Airborne Magnetic Data Collected to Detect UXO

2002 ◽  
Author(s):  
Jonathan E. Nyquist ◽  
Mathew S. Weikel ◽  
William E. Doll ◽  
T. Jeffrey Gamey
Keyword(s):  
Magnetic Data ◽  
Airborne Magnetic

scholarly journals A reconnaisance study to delineate the potential mineral zones around the schist belt areas Of Kano State, Nigeria using airborne magnetic data

2019 ◽  
Vol 11 (2) ◽  
pp. 14-21
Author(s):  
Sani Jamaluddeen Shehu ◽  
O. Aku Musa ◽  
Saleh Muhammad ◽  
Ali Bunawa Abdulrahim ◽  
Bolaji Sharafa Salihu
Keyword(s):  
Magnetic Data ◽  
Schist Belt ◽  
Airborne Magnetic
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