
TY  - JOUR
A1  - Meng, Zhaohai 
A1  - Li, Fengting 
A1  - Yu, Hao 
A1  - Ma, Lin 
A1  - L, Zhongi L 
T1  - Acceleration of 3D potential field data inversion using a BB iterative algorithm
JF  - ASEG Extended Abstracts
JO  - ASEG Extended Abstracts
Y1  - 2018
VL  - 2018
IS  - 1
SP  - 1
EP  - 4
KW  - 
UR  - https://doi.org/10.1071/ASEG2018ABP021 
N2  - As the big-data age arrives, the efficiency of three dimensional inversions of potential field data can be paid enough attention by scholars. A new inversion method is considered to deal with the large potential field data with a fast rate of convergence. Hence, in this paper, a fast inversion method is researched. And the gravity data is used as an example of potential field data to test the efficiency of our inversion method. To achieve this aim, the study region will be divided into huge amounts of rectangular prisms with unknown constant physical properties of rock. The traditional smooth inversion method is the main principle, and a new Barzilai-Borwein iterative algorithm is applied to ensure the rapid rate of convergence of the inversion method. To compare the rate of convergence of the BB (Barzilai-Borwein) iterative algorithm, the iterative gradient descent algorithm and the iterative conjugate gradient algorithm are used as the compared algorithms. To test high efficiency of the new fast developed inversion method, the large synthetic gravity data are performed. The contrast analysis results can easily reflect the high efficiency of our new inversion method. The great practical value of our inversion method is expounded by a real gravity data. Therefore, the new inversion method may have a great influence on the potential field data inversion. 
ER  -

