Acceleration of 3D potential field data inversion using a BB iterative algorithm
Zhaohai Meng, Fengting Li, Hao Yu, Lin Ma and Zhongi L L
ASEG Extended Abstracts
2018(1) 1 - 4
Published: 2018
Abstract
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.https://doi.org/10.1071/ASEG2018abP021
© ASEG 2018